diff --git a/src/sagemaker/image_uris.py b/src/sagemaker/image_uris.py
index 3ca7d2ed2e..8c3449e8c4 100644
--- a/src/sagemaker/image_uris.py
+++ b/src/sagemaker/image_uris.py
@@ -21,7 +21,7 @@
 from packaging.version import Version
 
 from sagemaker import utils
-from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION
+from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION, JUMPSTART_LOGGER
 from sagemaker.jumpstart.enums import JumpStartModelType
 from sagemaker.jumpstart.utils import is_jumpstart_model_input
 from sagemaker.spark import defaults
@@ -154,23 +154,27 @@ def retrieve(
             )
 
     if is_jumpstart_model_input(model_id, model_version):
+        if non_none_fields := {
+            key: value
+            for key, value in args.items()
+            if key in {"version", "framework", "container_version", "py_version"}
+            and value is not None
+        }:
+            JUMPSTART_LOGGER.info(
+                "Ignoring the following arguments when retrieving image uri "
+                "for JumpStart model id '%s': %s",
+                model_id,
+                str(non_none_fields),
+            )
         return artifacts._retrieve_image_uri(
-            model_id,
-            model_version,
-            image_scope,
-            hub_arn,
-            framework,
-            region,
-            version,
-            py_version,
-            instance_type,
-            accelerator_type,
-            container_version,
-            distribution,
-            base_framework_version,
-            training_compiler_config,
-            tolerate_vulnerable_model,
-            tolerate_deprecated_model,
+            model_id=model_id,
+            model_version=model_version,
+            image_scope=image_scope,
+            hub_arn=hub_arn,
+            region=region,
+            instance_type=instance_type,
+            tolerate_vulnerable_model=tolerate_vulnerable_model,
+            tolerate_deprecated_model=tolerate_deprecated_model,
             sagemaker_session=sagemaker_session,
             config_name=config_name,
             model_type=model_type,
diff --git a/src/sagemaker/jumpstart/artifacts/image_uris.py b/src/sagemaker/jumpstart/artifacts/image_uris.py
index 9079b094a4..8bcb205baa 100644
--- a/src/sagemaker/jumpstart/artifacts/image_uris.py
+++ b/src/sagemaker/jumpstart/artifacts/image_uris.py
@@ -14,14 +14,12 @@
 from __future__ import absolute_import
 
 from typing import Optional
-from sagemaker import image_uris
 from sagemaker.jumpstart.constants import (
     DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
 )
 from sagemaker.jumpstart.enums import (
     JumpStartModelType,
     JumpStartScriptScope,
-    ModelFramework,
 )
 from sagemaker.jumpstart.utils import (
     get_region_fallback,
@@ -35,16 +33,8 @@ def _retrieve_image_uri(
     model_version: str,
     image_scope: str,
     hub_arn: Optional[str] = None,
-    framework: Optional[str] = None,
     region: Optional[str] = None,
-    version: Optional[str] = None,
-    py_version: Optional[str] = None,
     instance_type: Optional[str] = None,
-    accelerator_type: Optional[str] = None,
-    container_version: Optional[str] = None,
-    distribution: Optional[str] = None,
-    base_framework_version: Optional[str] = None,
-    training_compiler_config: Optional[str] = None,
     tolerate_vulnerable_model: bool = False,
     tolerate_deprecated_model: bool = False,
     sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
@@ -66,30 +56,11 @@ def _retrieve_image_uri(
         image_scope (str): The image type, i.e. what it is used for.
             Valid values: "training", "inference", "eia". If ``accelerator_type`` is set,
             ``image_scope`` is ignored.
-        framework (str): The name of the framework or algorithm.
         region (str): The AWS region. (Default: None).
-        version (str): The framework or algorithm version. This is required if there is
-            more than one supported version for the given framework or algorithm.
-            (Default: None).
-        py_version (str): The Python version. This is required if there is
-            more than one supported Python version for the given framework version.
         instance_type (str): The SageMaker instance type. For supported types, see
             https://aws.amazon.com/sagemaker/pricing/instance-types. This is required if
             there are different images for different processor types.
             (Default: None).
-        accelerator_type (str): Elastic Inference accelerator type. For more, see
-            https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html.
-            (Default: None).
-        container_version (str): the version of docker image.
-            Ideally the value of parameter should be created inside the framework.
-            For custom use, see the list of supported container versions:
-            https://github.com/aws/deep-learning-containers/blob/master/available_images.md.
-            (Default: None).
-        distribution (dict): A dictionary with information on how to run distributed training.
-            (Default: None).
-        training_compiler_config (:class:`~sagemaker.training_compiler.TrainingCompilerConfig`):
-            A configuration class for the SageMaker Training Compiler.
-            (Default: None).
         tolerate_vulnerable_model (bool): True if vulnerable versions of model
             specifications should be tolerated (exception not raised). If False, raises an
             exception if the script used by this version of the model has dependencies with known
@@ -142,14 +113,12 @@ def _retrieve_image_uri(
             ecr_uri = model_specs.hosting_ecr_uri
             return ecr_uri
 
-        ecr_specs = model_specs.hosting_ecr_specs
-        if ecr_specs is None:
-            raise ValueError(
-                f"No inference ECR configuration found for JumpStart model ID '{model_id}' "
-                f"with {instance_type} instance type in {region}. "
-                "Please try another instance type or region."
-            )
-    elif image_scope == JumpStartScriptScope.TRAINING:
+        raise ValueError(
+            f"No inference ECR configuration found for JumpStart model ID '{model_id}' "
+            f"with {instance_type} instance type in {region}. "
+            "Please try another instance type or region."
+        )
+    if image_scope == JumpStartScriptScope.TRAINING:
         training_instance_type_variants = model_specs.training_instance_type_variants
         if training_instance_type_variants:
             image_uri = training_instance_type_variants.get_image_uri(
@@ -161,65 +130,10 @@ def _retrieve_image_uri(
             ecr_uri = model_specs.training_ecr_uri
             return ecr_uri
 
-        ecr_specs = model_specs.training_ecr_specs
-        if ecr_specs is None:
-            raise ValueError(
-                f"No training ECR configuration found for JumpStart model ID '{model_id}' "
-                f"with {instance_type} instance type in {region}. "
-                "Please try another instance type or region."
-            )
-    if framework is not None and framework != ecr_specs.framework:
-        raise ValueError(
-            f"Incorrect container framework '{framework}' for JumpStart model ID '{model_id}' "
-            f"and version '{model_version}'."
-        )
-
-    if version is not None and version != ecr_specs.framework_version:
-        raise ValueError(
-            f"Incorrect container framework version '{version}' for JumpStart model ID "
-            f"'{model_id}' and version '{model_version}'."
-        )
-
-    if py_version is not None and py_version != ecr_specs.py_version:
         raise ValueError(
-            f"Incorrect python version '{py_version}' for JumpStart model ID '{model_id}' "
-            f"and version '{model_version}'."
-        )
-
-    base_framework_version_override: Optional[str] = None
-    version_override: Optional[str] = None
-    if ecr_specs.framework == ModelFramework.HUGGINGFACE:
-        base_framework_version_override = ecr_specs.framework_version
-        version_override = ecr_specs.huggingface_transformers_version
-
-    if image_scope == JumpStartScriptScope.TRAINING:
-        return image_uris.get_training_image_uri(
-            region=region,
-            framework=ecr_specs.framework,
-            framework_version=version_override or ecr_specs.framework_version,
-            py_version=ecr_specs.py_version,
-            image_uri=None,
-            distribution=None,
-            compiler_config=None,
-            tensorflow_version=None,
-            pytorch_version=base_framework_version_override or base_framework_version,
-            instance_type=instance_type,
+            f"No training ECR configuration found for JumpStart model ID '{model_id}' "
+            f"with {instance_type} instance type in {region}. "
+            "Please try another instance type or region."
         )
-    if base_framework_version_override is not None:
-        base_framework_version_override = f"pytorch{base_framework_version_override}"
 
-    return image_uris.retrieve(
-        framework=ecr_specs.framework,
-        region=region,
-        version=version_override or ecr_specs.framework_version,
-        py_version=ecr_specs.py_version,
-        instance_type=instance_type,
-        hub_arn=hub_arn,
-        accelerator_type=accelerator_type,
-        image_scope=image_scope,
-        container_version=container_version,
-        distribution=distribution,
-        base_framework_version=base_framework_version_override or base_framework_version,
-        training_compiler_config=training_compiler_config,
-        config_name=config_name,
-    )
+    raise ValueError(f"Invalid scope: {image_scope}")
diff --git a/tests/integ/sagemaker/jumpstart/constants.py b/tests/integ/sagemaker/jumpstart/constants.py
index 27279feecf..1ffb1d8dc0 100644
--- a/tests/integ/sagemaker/jumpstart/constants.py
+++ b/tests/integ/sagemaker/jumpstart/constants.py
@@ -46,6 +46,7 @@ def _to_s3_path(filename: str, s3_prefix: Optional[str]) -> str:
 TRAINING_DATASET_MODEL_DICT = {
     ("huggingface-spc-bert-base-cased", "1.0.0"): ("training-datasets/QNLI-tiny/"),
     ("huggingface-spc-bert-base-cased", "1.2.3"): ("training-datasets/QNLI-tiny/"),
+    ("huggingface-spc-bert-base-cased", "2.0.3"): ("training-datasets/QNLI-tiny/"),
     ("huggingface-spc-bert-base-cased", "*"): ("training-datasets/QNLI-tiny/"),
     ("js-trainable-model", "*"): ("training-datasets/QNLI-tiny/"),
     ("meta-textgeneration-llama-2-7b", "*"): ("training-datasets/sec_amazon/"),
diff --git a/tests/integ/sagemaker/jumpstart/retrieve_uri/inference.py b/tests/integ/sagemaker/jumpstart/retrieve_uri/inference.py
index 4ad58153e9..7fbac1cdba 100644
--- a/tests/integ/sagemaker/jumpstart/retrieve_uri/inference.py
+++ b/tests/integ/sagemaker/jumpstart/retrieve_uri/inference.py
@@ -77,6 +77,10 @@ def package_artifacts(self):
 
         self.model_name = self.get_model_name()
 
+        if self.script_uri is None:
+            print("No script uri provided. Not performing prepack")
+            return self.model_uri
+
         cache_bucket_uri = f"s3://{get_test_artifact_bucket()}"
         repacked_model_uri = "/".join(
             [
@@ -147,16 +151,26 @@ def get_model_name(self) -> str:
         return f"{non_timestamped_name}{self.suffix}"
 
     def create_model(self) -> None:
+        primary_container = {
+            "Image": self.image_uri,
+            "Mode": "SingleModel",
+            "Environment": self.environment_variables,
+        }
+        if self.repacked_model_uri.endswith(".tar.gz"):
+            primary_container["ModelDataUrl"] = self.repacked_model_uri
+        else:
+            primary_container["ModelDataSource"] = {
+                "S3DataSource": {
+                    "S3Uri": self.repacked_model_uri,
+                    "S3DataType": "S3Prefix",
+                    "CompressionType": "None",
+                }
+            }
         self.sagemaker_client.create_model(
             ModelName=self.model_name,
             EnableNetworkIsolation=True,
             ExecutionRoleArn=self.execution_role,
-            PrimaryContainer={
-                "Image": self.image_uri,
-                "ModelDataUrl": self.repacked_model_uri,
-                "Mode": "SingleModel",
-                "Environment": self.environment_variables,
-            },
+            PrimaryContainer=primary_container,
         )
 
     def create_endpoint_config(self) -> None:
diff --git a/tests/integ/sagemaker/jumpstart/retrieve_uri/test_inference.py b/tests/integ/sagemaker/jumpstart/retrieve_uri/test_inference.py
index 550e2481cd..5f23428908 100644
--- a/tests/integ/sagemaker/jumpstart/retrieve_uri/test_inference.py
+++ b/tests/integ/sagemaker/jumpstart/retrieve_uri/test_inference.py
@@ -17,7 +17,6 @@
     InferenceJobLauncher,
 )
 from sagemaker import environment_variables, image_uris
-from sagemaker import script_uris
 from sagemaker import model_uris
 
 from tests.integ.sagemaker.jumpstart.constants import InferenceTabularDataname
@@ -31,8 +30,8 @@
 
 def test_jumpstart_inference_retrieve_functions(setup):
 
-    model_id, model_version = "catboost-classification-model", "1.0.0"
-    instance_type = "ml.m5.xlarge"
+    model_id, model_version = "catboost-classification-model", "2.1.6"
+    instance_type = "ml.m5.4xlarge"
 
     print("Starting inference...")
 
@@ -46,13 +45,6 @@ def test_jumpstart_inference_retrieve_functions(setup):
         tolerate_vulnerable_model=True,
     )
 
-    script_uri = script_uris.retrieve(
-        model_id=model_id,
-        model_version=model_version,
-        script_scope="inference",
-        tolerate_vulnerable_model=True,
-    )
-
     model_uri = model_uris.retrieve(
         model_id=model_id,
         model_version=model_version,
@@ -68,7 +60,7 @@ def test_jumpstart_inference_retrieve_functions(setup):
 
     inference_job = InferenceJobLauncher(
         image_uri=image_uri,
-        script_uri=script_uri,
+        script_uri=None,
         model_uri=model_uri,
         instance_type=instance_type,
         base_name="catboost",
diff --git a/tests/integ/sagemaker/jumpstart/retrieve_uri/test_transfer_learning.py b/tests/integ/sagemaker/jumpstart/retrieve_uri/test_transfer_learning.py
index 4e65cc5b58..7cb0f34fbf 100644
--- a/tests/integ/sagemaker/jumpstart/retrieve_uri/test_transfer_learning.py
+++ b/tests/integ/sagemaker/jumpstart/retrieve_uri/test_transfer_learning.py
@@ -33,7 +33,7 @@
 
 def test_jumpstart_transfer_learning_retrieve_functions(setup):
 
-    model_id, model_version = "huggingface-spc-bert-base-cased", "1.0.0"
+    model_id, model_version = "huggingface-spc-bert-base-cased", "2.0.3"
     training_instance_type = "ml.p3.2xlarge"
     inference_instance_type = "ml.p2.xlarge"
 
diff --git a/tests/unit/sagemaker/hyperparameters/jumpstart/test_default.py b/tests/unit/sagemaker/hyperparameters/jumpstart/test_default.py
index 565ebbce87..d0915b8881 100644
--- a/tests/unit/sagemaker/hyperparameters/jumpstart/test_default.py
+++ b/tests/unit/sagemaker/hyperparameters/jumpstart/test_default.py
@@ -46,7 +46,13 @@ def test_jumpstart_default_hyperparameters(
         model_version="*",
         sagemaker_session=mock_session,
     )
-    assert params == {"adam-learning-rate": "0.05", "batch-size": "4", "epochs": "3"}
+    assert params == {
+        "train_only_top_layer": "True",
+        "epochs": "5",
+        "learning_rate": "0.001",
+        "batch_size": "4",
+        "reinitialize_top_layer": "Auto",
+    }
 
     patched_get_model_specs.assert_called_once_with(
         region=region,
@@ -66,7 +72,13 @@ def test_jumpstart_default_hyperparameters(
         model_version="1.*",
         sagemaker_session=mock_session,
     )
-    assert params == {"adam-learning-rate": "0.05", "batch-size": "4", "epochs": "3"}
+    assert params == {
+        "train_only_top_layer": "True",
+        "epochs": "5",
+        "learning_rate": "0.001",
+        "batch_size": "4",
+        "reinitialize_top_layer": "Auto",
+    }
 
     patched_get_model_specs.assert_called_once_with(
         region=region,
@@ -88,12 +100,14 @@ def test_jumpstart_default_hyperparameters(
         sagemaker_session=mock_session,
     )
     assert params == {
-        "adam-learning-rate": "0.05",
-        "batch-size": "4",
-        "epochs": "3",
-        "sagemaker_container_log_level": "20",
-        "sagemaker_program": "transfer_learning.py",
+        "train_only_top_layer": "True",
+        "epochs": "5",
+        "learning_rate": "0.001",
+        "batch_size": "4",
+        "reinitialize_top_layer": "Auto",
         "sagemaker_submit_directory": "/opt/ml/input/data/code/sourcedir.tar.gz",
+        "sagemaker_program": "transfer_learning.py",
+        "sagemaker_container_log_level": "20",
     }
 
     patched_get_model_specs.assert_called_once_with(
diff --git a/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py b/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
index edf2cfca59..af5413ce6b 100644
--- a/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
+++ b/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
@@ -21,7 +21,7 @@
 from sagemaker.jumpstart.exceptions import JumpStartHyperparametersError
 from sagemaker.jumpstart.types import JumpStartHyperparameter
 
-from tests.unit.sagemaker.jumpstart.utils import get_spec_from_base_spec
+from tests.unit.sagemaker.jumpstart.utils import get_prototype_model_spec
 
 region = "us-west-2"
 mock_client = boto3.client("s3")
@@ -34,7 +34,7 @@ def test_jumpstart_validate_provided_hyperparameters(
     patched_get_model_specs, patched_validate_model_id_and_get_type
 ):
     def add_options_to_hyperparameter(*largs, **kwargs):
-        spec = get_spec_from_base_spec(*largs, **kwargs)
+        spec = get_prototype_model_spec(*largs, **kwargs)
         spec.hyperparameters.extend(
             [
                 JumpStartHyperparameter(
@@ -115,7 +115,7 @@ def add_options_to_hyperparameter(*largs, **kwargs):
     patched_get_model_specs.side_effect = add_options_to_hyperparameter
     patched_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
 
-    model_id, model_version = "pytorch-eqa-bert-base-cased", "*"
+    model_id, model_version = "mxnet-semseg-fcn-resnet50-ade", "*"
     region = "us-west-2"
 
     hyperparameter_to_test = {
@@ -412,7 +412,7 @@ def test_jumpstart_validate_algorithm_hyperparameters(
     patched_get_model_specs, patched_validate_model_id_and_get_type
 ):
     def add_options_to_hyperparameter(*largs, **kwargs):
-        spec = get_spec_from_base_spec(*largs, **kwargs)
+        spec = get_prototype_model_spec(*largs, **kwargs)
         spec.hyperparameters.append(
             JumpStartHyperparameter(
                 {
@@ -429,10 +429,11 @@ def add_options_to_hyperparameter(*largs, **kwargs):
     patched_get_model_specs.side_effect = add_options_to_hyperparameter
     patched_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
 
-    model_id, model_version = "pytorch-eqa-bert-base-cased", "*"
+    model_id, model_version = "mxnet-semseg-fcn-resnet50-ade", "*"
     region = "us-west-2"
 
     hyperparameter_to_test = {
+        "train-only-top-layer": "True",
         "adam-learning-rate": "0.05",
         "batch-size": "4",
         "epochs": "3",
@@ -488,13 +489,14 @@ def test_jumpstart_validate_all_hyperparameters(
     patched_get_model_specs, patched_validate_model_id_and_get_type
 ):
 
-    patched_get_model_specs.side_effect = get_spec_from_base_spec
+    patched_get_model_specs.side_effect = get_prototype_model_spec
     patched_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
 
-    model_id, model_version = "pytorch-eqa-bert-base-cased", "*"
+    model_id, model_version = "mxnet-semseg-fcn-resnet50-ade", "*"
     region = "us-west-2"
 
     hyperparameter_to_test = {
+        "train-only-top-layer": "True",
         "adam-learning-rate": "0.05",
         "batch-size": "4",
         "epochs": "3",
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_catboost.py b/tests/unit/sagemaker/image_uris/jumpstart/test_catboost.py
index 9261fd561e..98ddefb2c2 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_catboost.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_catboost.py
@@ -30,7 +30,7 @@ def test_jumpstart_catboost_image_uri(patched_get_model_specs, session):
     patched_get_model_specs.side_effect = get_prototype_model_spec
 
     model_id, model_version = "catboost-classification-model", "*"
-    instance_type = "ml.p2.xlarge"
+    instance_type = "ml.m5.xlarge"
     region = "us-west-2"
 
     model_specs = accessors.JumpStartModelsAccessor.get_model_specs(region, model_id, model_version)
@@ -55,7 +55,7 @@ def test_jumpstart_catboost_image_uri(patched_get_model_specs, session):
     ).serving_image_uri(region, instance_type)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.9.0-gpu-py38"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:2.0.1-cpu-py310"
 
     # training
     uri = image_uris.retrieve(
@@ -78,4 +78,4 @@ def test_jumpstart_catboost_image_uri(patched_get_model_specs, session):
     ).training_image_uri(region=region)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.9.0-gpu-py38"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.9.0-cpu-py38"
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_common.py b/tests/unit/sagemaker/image_uris/jumpstart/test_common.py
index cc3723c3c5..9a4febd0e4 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_common.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_common.py
@@ -47,7 +47,7 @@ def test_jumpstart_common_image_uri(
         image_scope="training",
         model_id="pytorch-ic-mobilenet-v2",
         model_version="*",
-        instance_type="ml.p2.xlarge",
+        instance_type="ml.m5.xlarge",
         sagemaker_session=mock_session,
     )
     patched_get_model_specs.assert_called_once_with(
@@ -70,7 +70,7 @@ def test_jumpstart_common_image_uri(
         image_scope="inference",
         model_id="pytorch-ic-mobilenet-v2",
         model_version="1.*",
-        instance_type="ml.p2.xlarge",
+        instance_type="ml.m5.xlarge",
         sagemaker_session=mock_session,
     )
     patched_get_model_specs.assert_called_once_with(
@@ -93,7 +93,7 @@ def test_jumpstart_common_image_uri(
         image_scope="training",
         model_id="pytorch-ic-mobilenet-v2",
         model_version="*",
-        instance_type="ml.p2.xlarge",
+        instance_type="ml.m5.xlarge",
         sagemaker_session=mock_session,
     )
     patched_get_model_specs.assert_called_once_with(
@@ -116,7 +116,7 @@ def test_jumpstart_common_image_uri(
         image_scope="inference",
         model_id="pytorch-ic-mobilenet-v2",
         model_version="1.*",
-        instance_type="ml.p2.xlarge",
+        instance_type="ml.m5.xlarge",
         sagemaker_session=mock_session,
     )
     patched_get_model_specs.assert_called_once_with(
@@ -137,7 +137,7 @@ def test_jumpstart_common_image_uri(
             image_scope="BAD_SCOPE",
             model_id="pytorch-ic-mobilenet-v2",
             model_version="*",
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
         )
 
     with pytest.raises(KeyError):
@@ -147,7 +147,7 @@ def test_jumpstart_common_image_uri(
             image_scope="training",
             model_id="blah",
             model_version="*",
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
         )
 
     with pytest.raises(ValueError):
@@ -157,7 +157,7 @@ def test_jumpstart_common_image_uri(
             image_scope="training",
             model_id="pytorch-ic-mobilenet-v2",
             model_version="*",
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
         )
 
     with pytest.raises(ValueError):
@@ -166,7 +166,7 @@ def test_jumpstart_common_image_uri(
             region="us-west-2",
             model_id="pytorch-ic-mobilenet-v2",
             model_version="*",
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
         )
 
     with pytest.raises(ValueError):
@@ -175,7 +175,7 @@ def test_jumpstart_common_image_uri(
             region="us-west-2",
             image_scope="training",
             model_version="*",
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
         )
 
     with pytest.raises(ValueError):
@@ -184,5 +184,56 @@ def test_jumpstart_common_image_uri(
             framework=None,
             image_scope="training",
             model_id="pytorch-ic-mobilenet-v2",
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
         )
+
+
+@patch("sagemaker.image_uris.JUMPSTART_LOGGER.info")
+@patch("sagemaker.jumpstart.utils.validate_model_id_and_get_type")
+@patch("sagemaker.jumpstart.artifacts.image_uris.verify_model_region_and_return_specs")
+@patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
+def test_jumpstart_image_uri_logging_extra_fields(
+    patched_get_model_specs,
+    patched_verify_model_region_and_return_specs,
+    patched_validate_model_id_and_get_type,
+    patched_info_log,
+):
+
+    patched_verify_model_region_and_return_specs.side_effect = verify_model_region_and_return_specs
+    patched_get_model_specs.side_effect = get_spec_from_base_spec
+    patched_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
+
+    region = "us-west-2"
+    mock_client = boto3.client("s3")
+    mock_session = Mock(s3_client=mock_client, boto_region_name=region)
+
+    image_uris.retrieve(
+        framework=None,
+        region="us-west-2",
+        image_scope="training",
+        model_id="pytorch-ic-mobilenet-v2",
+        model_version="*",
+        instance_type="ml.m5.xlarge",
+        sagemaker_session=mock_session,
+    )
+
+    patched_info_log.assert_not_called()
+
+    image_uris.retrieve(
+        framework="framework",
+        container_version="1.2.3",
+        region="us-west-2",
+        image_scope="training",
+        model_id="pytorch-ic-mobilenet-v2",
+        model_version="*",
+        instance_type="ml.m5.xlarge",
+        sagemaker_session=mock_session,
+    )
+
+    patched_info_log.assert_called_once_with(
+        "Ignoring the following arguments "
+        "when retrieving image uri for "
+        "JumpStart model id '%s': %s",
+        "pytorch-ic-mobilenet-v2",
+        "{'framework': 'framework', 'container_version': '1.2.3'}",
+    )
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_huggingface.py b/tests/unit/sagemaker/image_uris/jumpstart/test_huggingface.py
index 1ce213cd27..0f426103e8 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_huggingface.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_huggingface.py
@@ -28,7 +28,8 @@ def test_jumpstart_huggingface_image_uri(patched_get_model_specs, session):
     patched_get_model_specs.side_effect = get_prototype_model_spec
 
     model_id, model_version = "huggingface-spc-bert-base-cased", "*"
-    instance_type = "ml.p2.xlarge"
+    instance_type = "ml.m5.xlarge"
+    training_instance_type = "ml.p3.2xlarge"
     region = "us-west-2"
 
     model_specs = accessors.JumpStartModelsAccessor.get_model_specs(region, model_id, model_version)
@@ -55,7 +56,7 @@ def test_jumpstart_huggingface_image_uri(patched_get_model_specs, session):
 
     assert (
         uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:"
-        "1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
+        "1.7.1-transformers4.6.1-cpu-py36-ubuntu18.04"
     )
 
     # training
@@ -65,7 +66,7 @@ def test_jumpstart_huggingface_image_uri(patched_get_model_specs, session):
         image_scope="training",
         model_id=model_id,
         model_version=model_version,
-        instance_type=instance_type,
+        instance_type=training_instance_type,
     )
 
     framework_class_uri = HuggingFace(
@@ -75,7 +76,7 @@ def test_jumpstart_huggingface_image_uri(patched_get_model_specs, session):
         entry_point="some_entry_point",
         transformers_version=model_specs.training_ecr_specs.huggingface_transformers_version,
         pytorch_version=model_specs.training_ecr_specs.framework_version,
-        instance_type=instance_type,
+        instance_type=training_instance_type,
         instance_count=1,
         sagemaker_session=session,
     ).training_image_uri(region=region)
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_lightgbm.py b/tests/unit/sagemaker/image_uris/jumpstart/test_lightgbm.py
index e907a19b51..159d801867 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_lightgbm.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_lightgbm.py
@@ -28,7 +28,7 @@ def test_jumpstart_lightgbm_image_uri(patched_get_model_specs, session):
     patched_get_model_specs.side_effect = get_prototype_model_spec
 
     model_id, model_version = "lightgbm-classification-model", "*"
-    instance_type = "ml.p2.xlarge"
+    instance_type = "ml.m5.xlarge"
     region = "us-west-2"
 
     model_specs = accessors.JumpStartModelsAccessor.get_model_specs(region, model_id, model_version)
@@ -53,7 +53,7 @@ def test_jumpstart_lightgbm_image_uri(patched_get_model_specs, session):
     ).serving_image_uri(region, instance_type)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.9.0-gpu-py38"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:2.0.1-cpu-py310"
 
     # training
     uri = image_uris.retrieve(
@@ -76,4 +76,4 @@ def test_jumpstart_lightgbm_image_uri(patched_get_model_specs, session):
     ).training_image_uri(region=region)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.9.0-gpu-py38"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.9.0-cpu-py38"
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_mxnet.py b/tests/unit/sagemaker/image_uris/jumpstart/test_mxnet.py
index 9fd09d47d9..4d09c36b68 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_mxnet.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_mxnet.py
@@ -28,7 +28,7 @@ def test_jumpstart_mxnet_image_uri(patched_get_model_specs, session):
     patched_get_model_specs.side_effect = get_prototype_model_spec
 
     model_id, model_version = "mxnet-semseg-fcn-resnet50-ade", "*"
-    instance_type = "ml.p2.xlarge"
+    instance_type = "ml.m5.xlarge"
     region = "us-west-2"
 
     model_specs = accessors.JumpStartModelsAccessor.get_model_specs(region, model_id, model_version)
@@ -53,7 +53,7 @@ def test_jumpstart_mxnet_image_uri(patched_get_model_specs, session):
     ).serving_image_uri(region, instance_type)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:1.7.0-gpu-py3"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:1.9.0-cpu-py38"
 
     # training
     uri = image_uris.retrieve(
@@ -76,4 +76,4 @@ def test_jumpstart_mxnet_image_uri(patched_get_model_specs, session):
     ).training_image_uri(region=region)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:1.7.0-gpu-py3"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:1.9.0-cpu-py38"
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_pytorch.py b/tests/unit/sagemaker/image_uris/jumpstart/test_pytorch.py
index a94801da10..24e759e6bc 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_pytorch.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_pytorch.py
@@ -27,7 +27,7 @@ def test_jumpstart_pytorch_image_uri(patched_get_model_specs, session):
 
     patched_get_model_specs.side_effect = get_prototype_model_spec
 
-    model_id, model_version = "pytorch-eqa-bert-base-cased", "*"
+    model_id, model_version = "pytorch-ic-mobilenet-v2", "*"
     instance_type = "ml.p2.xlarge"
     region = "us-west-2"
 
@@ -53,7 +53,7 @@ def test_jumpstart_pytorch_image_uri(patched_get_model_specs, session):
     ).serving_image_uri(region, instance_type)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.5.0-gpu-py3"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.10.0-gpu-py38"
 
     # training
     uri = image_uris.retrieve(
@@ -76,4 +76,4 @@ def test_jumpstart_pytorch_image_uri(patched_get_model_specs, session):
     ).training_image_uri(region=region)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.5.0-gpu-py3"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38"
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_sklearn.py b/tests/unit/sagemaker/image_uris/jumpstart/test_sklearn.py
index 1410c59bb6..af0614c465 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_sklearn.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_sklearn.py
@@ -29,7 +29,7 @@ def test_jumpstart_sklearn_image_uri(patched_get_model_specs, session):
     patched_get_model_specs.side_effect = get_prototype_model_spec
 
     model_id, model_version = "sklearn-classification-linear", "*"
-    instance_type = "ml.m2.xlarge"
+    instance_type = "ml.m5.xlarge"
     region = "us-west-2"
 
     model_specs = accessors.JumpStartModelsAccessor.get_model_specs(region, model_id, model_version)
@@ -53,9 +53,15 @@ def test_jumpstart_sklearn_image_uri(patched_get_model_specs, session):
         sagemaker_session=session,
     ).serving_image_uri(region, instance_type)
 
-    assert uri == framework_class_uri
+    # framework classes dont use digest.
     assert (
-        uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:0.23-1-cpu-py3"
+        framework_class_uri
+        == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:1.2-1"
+        "-cpu-py3"
+    )
+    assert (
+        uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn@"
+        "sha256:e09bbb7686077a1db23d316b699020a786a6e1636b2b89384be9651368c40f95"
     )
 
     # training
@@ -79,9 +85,14 @@ def test_jumpstart_sklearn_image_uri(patched_get_model_specs, session):
         sagemaker_session=session,
     ).training_image_uri(region=region)
 
-    assert uri == framework_class_uri
+    # framework classes dont use digest.
+    assert (
+        framework_class_uri
+        == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:1.2-1-cpu-py3"
+    )
     assert (
-        uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:0.23-1-cpu-py3"
+        uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn"
+        "@sha256:e09bbb7686077a1db23d316b699020a786a6e1636b2b89384be9651368c40f95"
     )
 
     with pytest.raises(ValueError):
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_tensorflow.py b/tests/unit/sagemaker/image_uris/jumpstart/test_tensorflow.py
index c924615212..cfe57f4053 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_tensorflow.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_tensorflow.py
@@ -52,7 +52,7 @@ def test_jumpstart_tensorflow_image_uri(patched_get_model_specs, session):
     ).serving_image_uri(region, instance_type)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:2.3-gpu"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:2.8-gpu"
 
     # training
     uri = image_uris.retrieve(
@@ -75,4 +75,4 @@ def test_jumpstart_tensorflow_image_uri(patched_get_model_specs, session):
     ).training_image_uri(region=region)
 
     assert uri == framework_class_uri
-    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:2.3-gpu-py37"
+    assert uri == "763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:2.9-gpu-py39"
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_variants.py b/tests/unit/sagemaker/image_uris/jumpstart/test_variants.py
index 20547caca3..80bf54f722 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_variants.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_variants.py
@@ -52,9 +52,8 @@ def test_jumpstart_variants_image_uri(
         instance_type="ml.c2.xlarge",
     )
 
-    assert (
-        "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.5.0-cpu-py3"
-        == image_uris.retrieve(
+    with pytest.raises(ValueError):
+        image_uris.retrieve(
             framework=None,
             region="us-west-2",
             image_scope="inference",
@@ -62,7 +61,6 @@ def test_jumpstart_variants_image_uri(
             model_version="*",
             instance_type="ml.c200000.xlarge",
         )
-    )
 
     with pytest.raises(ValueError):
         image_uris.retrieve(
@@ -74,9 +72,8 @@ def test_jumpstart_variants_image_uri(
             instance_type="ml.c2.xlarge",
         )
 
-    assert (
-        "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.5.0-gpu-py3"
-        == image_uris.retrieve(
+    with pytest.raises(ValueError):
+        image_uris.retrieve(
             framework=None,
             region="us-west-2",
             image_scope="training",
@@ -84,4 +81,3 @@ def test_jumpstart_variants_image_uri(
             model_version="*",
             instance_type="ml.g4dn.2xlarge",
         )
-    )
diff --git a/tests/unit/sagemaker/image_uris/jumpstart/test_xgboost.py b/tests/unit/sagemaker/image_uris/jumpstart/test_xgboost.py
index 5da3b71176..7817980bac 100644
--- a/tests/unit/sagemaker/image_uris/jumpstart/test_xgboost.py
+++ b/tests/unit/sagemaker/image_uris/jumpstart/test_xgboost.py
@@ -52,8 +52,15 @@ def test_jumpstart_xgboost_image_uri(patched_get_model_specs, session):
         sagemaker_session=session,
     ).serving_image_uri(region, instance_type)
 
-    assert uri == framework_class_uri
-    assert uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:1.3-1"
+    # framework classes dont use digest
+    assert (
+        framework_class_uri
+        == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:1.7-1"
+    )
+    assert (
+        uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost@sha256:"
+        "ba417ec6d8d3e0c6b5f463bc9202e3b498b42260a29b61875f34beb6d99d8444"
+    )
 
     # training
     uri = image_uris.retrieve(
@@ -76,5 +83,12 @@ def test_jumpstart_xgboost_image_uri(patched_get_model_specs, session):
         sagemaker_session=session,
     ).training_image_uri(region=region)
 
-    assert uri == framework_class_uri
-    assert uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:1.3-1"
+    # framework classes dont use digest
+    assert (
+        framework_class_uri
+        == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:1.7-1"
+    )
+    assert (
+        uri == "246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost"
+        "@sha256:ba417ec6d8d3e0c6b5f463bc9202e3b498b42260a29b61875f34beb6d99d8444"
+    )
diff --git a/tests/unit/sagemaker/instance_types/jumpstart/test_instance_types.py b/tests/unit/sagemaker/instance_types/jumpstart/test_instance_types.py
index 5db149c4c3..2b73766ea4 100644
--- a/tests/unit/sagemaker/instance_types/jumpstart/test_instance_types.py
+++ b/tests/unit/sagemaker/instance_types/jumpstart/test_instance_types.py
@@ -43,7 +43,7 @@ def test_jumpstart_instance_types(patched_get_model_specs, patched_validate_mode
         scope="training",
         sagemaker_session=mock_session,
     )
-    assert default_training_instance_types == "ml.p3.2xlarge"
+    assert default_training_instance_types == "ml.m5.xlarge"
 
     patched_get_model_specs.assert_called_once_with(
         region=region,
@@ -64,7 +64,7 @@ def test_jumpstart_instance_types(patched_get_model_specs, patched_validate_mode
         scope="inference",
         sagemaker_session=mock_session,
     )
-    assert default_inference_instance_types == "ml.p2.xlarge"
+    assert default_inference_instance_types == "ml.m5.large"
 
     patched_get_model_specs.assert_called_once_with(
         region=region,
@@ -85,13 +85,7 @@ def test_jumpstart_instance_types(patched_get_model_specs, patched_validate_mode
         scope="training",
         sagemaker_session=mock_session,
     )
-    assert default_training_instance_types == [
-        "ml.p3.2xlarge",
-        "ml.p2.xlarge",
-        "ml.g4dn.2xlarge",
-        "ml.m5.xlarge",
-        "ml.c5.2xlarge",
-    ]
+    assert default_training_instance_types == ["ml.m5.xlarge", "ml.c5.2xlarge", "ml.m4.xlarge"]
 
     patched_get_model_specs.assert_called_once_with(
         region=region,
@@ -113,13 +107,12 @@ def test_jumpstart_instance_types(patched_get_model_specs, patched_validate_mode
         sagemaker_session=mock_session,
     )
     assert default_inference_instance_types == [
-        "ml.p2.xlarge",
-        "ml.p3.2xlarge",
-        "ml.g4dn.xlarge",
         "ml.m5.large",
         "ml.m5.xlarge",
         "ml.c5.xlarge",
         "ml.c5.2xlarge",
+        "ml.m4.large",
+        "ml.m4.xlarge",
     ]
 
     patched_get_model_specs.assert_called_once_with(
diff --git a/tests/unit/sagemaker/jumpstart/constants.py b/tests/unit/sagemaker/jumpstart/constants.py
index d22428f4f0..59f38bd189 100644
--- a/tests/unit/sagemaker/jumpstart/constants.py
+++ b/tests/unit/sagemaker/jumpstart/constants.py
@@ -12,8 +12,281 @@
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
 
+# flake8: noqa: E501
 
 SPECIAL_MODEL_SPECS_DICT = {
+    "js-model-class-model-prepacked": {
+        "model_id": "huggingface-txt2img-conflictx-complex-lineart",
+        "url": "https://huggingface.co/Conflictx/Complex-Lineart",
+        "version": "2.0.3",
+        "min_sdk_version": "2.189.0",
+        "training_supported": False,
+        "incremental_training_supported": False,
+        "hosting_ecr_specs": {
+            "framework": "huggingface",
+            "framework_version": "1.10.2",
+            "py_version": "py38",
+            "huggingface_transformers_version": "4.17.0",
+        },
+        "hosting_artifact_key": "huggingface-txt2img/huggingface-txt2img-conflictx-complex-lineart/artifacts/inference/v1.0.0/",
+        "hosting_script_key": "source-directory-tarballs/huggingface/inference/txt2img/v1.1.0/sourcedir.tar.gz",
+        "hosting_prepacked_artifact_key": "huggingface-txt2img/huggingface-txt2img-conflictx-complex-lineart/artifacts/inference-prepack/v1.0.0/",
+        "hosting_prepacked_artifact_version": "1.0.0",
+        "hosting_use_script_uri": False,
+        "inference_vulnerable": False,
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@@ -2188,21 +2461,20 @@
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         "url": "https://huggingface.co/tiiuae/falcon-180B",
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         "hosting_script_key": "source-directory-tarballs/huggingface/inference/llm/v1.0.1/sourcedir.tar.gz",
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-        "-huggingface-llm-falcon-180b-bf16.tar.gz",
-        "hosting_prepacked_artifact_version": "1.0.1",
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         "inference_dependencies": [],
@@ -2299,7 +2571,7 @@
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         "metrics": [],
         "default_inference_instance_type": "ml.p4de.24xlarge",
-        "supported_inference_instance_types": ["ml.p4de.24xlarge"],
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         "deploy_kwargs": {
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@@ -2316,43 +2588,281 @@
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+                    "inputs": '"I hate it when my phone battery dies."\nSentiment: Negative\n###\nTweet: "My day has been :+1:"\nSentiment: Positive\n###\nTweet: "This is the link to the article"\nSentiment: Neutral\n###\nTweet: "This new music video was incredibile"\nSentiment:',
+                    "parameters": {
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+                    "inputs": "What is the recipe for a delicious lemon cheesecake?",
+                    "parameters": {
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+                    "inputs": "Starting today, the state-of-the-art Falcon 40B foundation model from Technology\nInnovation Institute (TII) is available on Amazon SageMaker JumpStart, SageMaker's machine learning (ML) hub\nthat offers pre-trained models, built-in algorithms, and pre-built solution templates to help you quickly get\nstarted with ML. You can deploy and use this Falcon LLM with a few clicks in SageMaker Studio or\nprogrammatically through the SageMaker Python SDK.\nFalcon 40B is a 40-billion-parameter large language model (LLM) available under the Apache 2.0 license that\nranked #1 in Hugging Face Open LLM leaderboard, which tracks, ranks, and evaluates LLMs across multiple\nbenchmarks to identify top performing models. Since its release in May 2023, Falcon 40B has demonstrated\nexceptional performance without specialized fine-tuning. To make it easier for customers to access this\nstate-of-the-art model, AWS has made Falcon 40B available to customers via Amazon SageMaker JumpStart.\nNow customers can quickly and easily deploy their own Falcon 40B model and customize it to fit their specific\nneeds for applications such as translation, question answering, and summarizing information.\nFalcon 40B are generally available today through Amazon SageMaker JumpStart in US East (Ohio),\nUS East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Mumbai),\nEurope (London), Europe (Frankfurt), Europe (Ireland), and Canada (Central),\nwith availability in additional AWS Regions coming soon. To learn how to use this new feature,\nplease see SageMaker JumpStart documentation, the Introduction to SageMaker JumpStart \u2013\nText Generation with Falcon LLMs example notebook, and the blog Technology Innovation Institute trains\nthe state-of-the-art Falcon LLM 40B foundation model on Amazon SageMaker. Summarize the article above:",
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+                        "decoder_input_details": True,
+                        "details": True,
+                    },
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+                "g6": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
+                "g6e": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
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+                "ml.p4d.24xlarge": {"properties": {"environment_variables": {"SM_NUM_GPUS": "8"}}},
+                "ml.p4de.24xlarge": {
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+                        "environment_variables": {"SM_NUM_GPUS": "8"},
+                        "resource_requirements": {"min_memory_mb": 589824, "num_accelerators": 8},
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+                "ml.p5.48xlarge": {
+                    "properties": {
+                        "resource_requirements": {"min_memory_mb": 1048576, "num_accelerators": 8}
+                    }
+                },
+                "ml.g5.48xlarge": {"properties": {"environment_variables": {"SM_NUM_GPUS": "80"}}},
+                "ml.p4d.24xlarge": {
+                    "properties": {
+                        "environment_variables": {
+                            "YODEL": "NACEREMA",
+                        }
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+                },
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+        "hosting_resource_requirements": {"min_memory_mb": 589824, "num_accelerators": 8},
+        "dynamic_container_deployment_supported": True,
+        "bedrock_console_supported": True,
+        "bedrock_io_mapping_id": "tgi_default_1.0.0",
+    },
+    "inference-instance-types-variant-model": {
+        "model_id": "huggingface-llm-falcon-180b-bf16",
+        "url": "https://huggingface.co/tiiuae/falcon-180B",
+        "version": "1.0.0",
+        "min_sdk_version": "2.175.0",
+        "training_supported": True,
+        "incremental_training_supported": False,
+        "hosting_ecr_specs": {
             "framework": "huggingface-llm",
             "framework_version": "0.9.3",
             "py_version": "py39",
@@ -4039,106 +4549,64 @@
     "model-artifact-variant-model": {
         "model_id": "pytorch-ic-mobilenet-v2",
         "url": "https://pytorch.org/hub/pytorch_vision_mobilenet_v2/",
-        "version": "1.0.0",
-        "min_sdk_version": "2.49.0",
+        "version": "3.0.6",
+        "min_sdk_version": "2.189.0",
         "training_supported": True,
         "incremental_training_supported": True,
         "hosting_ecr_specs": {
             "framework": "pytorch",
-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework_version": "1.10.0",
+            "py_version": "py38",
         },
-        "hosting_instance_type_variants": {
-            "regional_aliases": {
-                "us-west-2": {
-                    "gpu_image_uri": "763104351884.dkr.ecr.us-west-2.amazonaws.com/"
-                    "huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
-                    "cpu_image_uri": "867930986793.dkr.us-west-2.amazonaws.com/cpu-blah",
-                }
+        "hosting_artifact_key": "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference/v2.0.0/",
+        "hosting_script_key": "source-directory-tarballs/pytorch/inference/ic/v2.0.0/sourcedir.tar.gz",
+        "hosting_prepacked_artifact_key": "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference-prepack/v1.0.0/",
+        "hosting_prepacked_artifact_version": "1.0.0",
+        "hosting_use_script_uri": False,
+        "inference_vulnerable": False,
+        "inference_dependencies": [],
+        "inference_vulnerabilities": [],
+        "training_vulnerable": False,
+        "training_dependencies": ["sagemaker_jumpstart_prepack_script_utilities==1.0.0"],
+        "training_vulnerabilities": [],
+        "deprecated": False,
+        "hyperparameters": [
+            {
+                "name": "train_only_top_layer",
+                "type": "text",
+                "default": "True",
+                "options": ["True", "False"],
+                "scope": "algorithm",
             },
-            "variants": {
-                "p2": {
-                    "regional_properties": {"image_uri": "$gpu_image_uri"},
-                    "properties": {"prepacked_artifact_key": "hello-world-1"},
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-                },
-                "ml.g5.12xlarge": {
-                    "properties": {"environment_variables": {"TENSOR_PARALLEL_DEGREE": "4"}}
-                },
+            {
+                "name": "epochs",
+                "type": "int",
+                "default": 5,
+                "min": 1,
+                "max": 1000,
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             },
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-                    "cpu_image_uri": "867930986793.dkr.us-west-2.amazonaws.com/cpu-blah",
-                }
+            {
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+                "type": "float",
+                "default": 0.001,
+                "min": 1e-08,
+                "max": 1,
+                "scope": "algorithm",
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-        "training_model_package_artifact_uris": None,
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-        "hosting_model_package_arns": None,
-        "hosting_eula_key": None,
-        "hyperparameters": [
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-                "name": "epochs",
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@@ -4218,49 +4695,383 @@
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-            "regex==2022.7.9",
-            "tokenizers==0.13.2",
-            "transformers==4.26.0",
-        ],
-        "inference_vulnerabilities": [],
-        "training_vulnerable": False,
+        "training_vulnerable": True,
         "training_dependencies": [
-            "Brotli==1.0.9",
-            "absl-py==1.4.0",
-            "accelerate==0.16.0",
-            "datasets==2.9.0",
-            "deepspeed==0.8.0",
-            "evaluate==0.4.0",
-            "hjson==3.1.0",
-            "huggingface_hub==0.13.3",
+            "accelerate==0.21.0",
+            "bitsandbytes==0.39.1",
+            "black==23.7.0",
+            "brotli==1.0.9",
+            "datasets==2.14.1",
+            "fire==0.5.0",
             "inflate64==0.3.1",
+            "loralib==0.1.1",
             "multivolumefile==0.2.3",
-            "ninja==1.11.1",
-            "nltk==3.8.1",
-            "psutil==5.9.4",
-            "py-cpuinfo==9.0.0",
-            "py7zr==0.20.4",
+            "mypy-extensions==1.0.0",
+            "pathspec==0.11.1",
+            "peft==0.4.0",
+            "py7zr==0.20.5",
             "pybcj==1.0.1",
-            "pycryptodomex==3.17",
-            "pydantic==1.10.2",
+            "pycryptodomex==3.18.0",
             "pyppmd==1.0.0",
-            "pyzstd==0.15.4",
-            "rouge-score==0.1.2",
-            "sagemaker_jumpstart_script_utilities==1.1.4",
-            "sagemaker_jumpstart_tabular_script_utilities==1.0.0",
-            "tensorboardX==2.6",
+            "pytorch-triton==2.1.0+6e4932cda8",
+            "pyzstd==0.15.9",
+            "safetensors==0.3.1",
+            "sagemaker_jumpstart_huggingface_script_utilities==1.1.3",
+            "sagemaker_jumpstart_script_utilities==1.1.9",
+            "scipy==1.11.1",
+            "termcolor==2.3.0",
             "texttable==1.6.7",
-            "transformers==4.26.0",
+            "tokenize-rt==5.1.0",
+            "tokenizers==0.13.3",
+            "torch==2.2.0.dev20231104+cu118",
+            "transformers==4.31.0",
         ],
-        "training_vulnerabilities": [],
+        "training_vulnerabilities": ["transformers==4.31.0"],
         "deprecated": False,
+        "deprecate_warn_message": "For forward compatibility, pin to model_version='2.*' in your JumpStartModel or JumpStartEstimator definitions. Note that major version upgrades may have different EULA acceptance terms and input/output signatures.",
         "hyperparameters": [
             {
-                "name": "epochs",
-                "type": "int",
-                "default": 1,
-                "min": 1,
-                "max": 1000,
+                "name": "int8_quantization",
+                "type": "text",
+                "default": "False",
+                "options": ["True", "False"],
                 "scope": "algorithm",
             },
             {
-                "name": "seed",
-                "type": "int",
-                "default": 42,
-                "min": 1,
-                "max": 1000,
+                "name": "enable_fsdp",
+                "type": "text",
+                "default": "True",
+                "options": ["True", "False"],
                 "scope": "algorithm",
             },
             {
-                "name": "batch_size",
+                "name": "epoch",
                 "type": "int",
-                "default": 64,
+                "default": 1,
                 "min": 1,
-                "max": 1024,
+                "max": 1000,
                 "scope": "algorithm",
             },
             {
@@ -4639,668 +5403,659 @@
                 "max": 1,
                 "scope": "algorithm",
             },
+            {"name": "lora_r", "type": "int", "default": 8, "min": 1, "scope": "algorithm"},
+            {"name": "lora_alpha", "type": "int", "default": 32, "min": 1, "scope": "algorithm"},
             {
-                "name": "validation_split_ratio",
+                "name": "lora_dropout",
                 "type": "float",
                 "default": 0.05,
                 "min": 0,
                 "max": 1,
                 "scope": "algorithm",
             },
-            {"name": "train_data_split_seed", "type": "int", "default": 0, "scope": "algorithm"},
             {
-                "name": "sagemaker_submit_directory",
+                "name": "instruction_tuned",
                 "type": "text",
-                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
-                "scope": "container",
+                "default": "False",
+                "options": ["True", "False"],
+                "scope": "algorithm",
             },
             {
-                "name": "sagemaker_program",
+                "name": "chat_dataset",
                 "type": "text",
-                "default": "transfer_learning.py",
-                "scope": "container",
+                "default": "True",
+                "options": ["True", "False"],
+                "scope": "algorithm",
             },
             {
-                "name": "sagemaker_container_log_level",
+                "name": "add_input_output_demarcation_key",
                 "type": "text",
-                "default": "20",
-                "scope": "container",
+                "default": "True",
+                "options": ["True", "False"],
+                "scope": "algorithm",
             },
-        ],
-        "training_script_key": "source-directory-tarballs/huggingface/transfer_learning/text2text/"
-        "v1.1.0/sourcedir.tar.gz",
-        "training_prepacked_script_key": "source-directory-tarballs/huggingface/transfer_learning/"
-        "text2text/prepack/v1.0.1/sourcedir.tar.gz",
-        "training_prepacked_script_version": "1.0.1",
-        "training_ecr_specs": {
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-            "framework_version": "1.10.2",
-            "py_version": "py38",
-            "huggingface_transformers_version": "4.17.0",
-        },
-        "training_artifact_key": "huggingface-training/train-huggingface-text2text-flan-t5-base.tar.gz",
-        "inference_environment_variables": [
             {
-                "name": "SAGEMAKER_PROGRAM",
-                "type": "text",
-                "default": "inference.py",
-                "scope": "container",
-                "required_for_model_class": True,
+                "name": "per_device_train_batch_size",
+                "type": "int",
+                "default": 1,
+                "min": 1,
+                "max": 1000,
+                "scope": "algorithm",
             },
             {
-                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
-                "type": "text",
-                "default": "/opt/ml/model/code",
-                "scope": "container",
-                "required_for_model_class": False,
+                "name": "per_device_eval_batch_size",
+                "type": "int",
+                "default": 1,
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+                "max": 1000,
+                "scope": "algorithm",
             },
             {
-                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
-                "type": "text",
-                "default": "20",
-                "scope": "container",
-                "required_for_model_class": False,
+                "name": "max_train_samples",
+                "type": "int",
+                "default": -1,
+                "min": -1,
+                "scope": "algorithm",
             },
             {
-                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
-                "type": "text",
-                "default": "3600",
-                "scope": "container",
-                "required_for_model_class": False,
+                "name": "max_val_samples",
+                "type": "int",
+                "default": -1,
+                "min": -1,
+                "scope": "algorithm",
             },
             {
-                "name": "ENDPOINT_SERVER_TIMEOUT",
+                "name": "seed",
                 "type": "int",
-                "default": 3600,
-                "scope": "container",
-                "required_for_model_class": True,
+                "default": 10,
+                "min": 1,
+                "max": 1000,
+                "scope": "algorithm",
             },
             {
-                "name": "MODEL_CACHE_ROOT",
+                "name": "max_input_length",
+                "type": "int",
+                "default": -1,
+                "min": -1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "validation_split_ratio",
+                "type": "float",
+                "default": 0.2,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "train_data_split_seed",
+                "type": "int",
+                "default": 0,
+                "min": 0,
+                "scope": "algorithm",
+            },
+            {
+                "name": "preprocessing_num_workers",
                 "type": "text",
-                "default": "/opt/ml/model",
+                "default": "None",
+                "scope": "algorithm",
+            },
+            {
+                "name": "sagemaker_submit_directory",
+                "type": "text",
+                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
                 "scope": "container",
-                "required_for_model_class": True,
             },
             {
-                "name": "SAGEMAKER_ENV",
+                "name": "sagemaker_program",
                 "type": "text",
-                "default": "1",
+                "default": "transfer_learning.py",
                 "scope": "container",
-                "required_for_model_class": True,
             },
             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
-                "type": "int",
-                "default": 1,
+                "name": "sagemaker_container_log_level",
+                "type": "text",
+                "default": "20",
                 "scope": "container",
-                "required_for_model_class": True,
             },
         ],
+        "training_script_key": "source-directory-tarballs/meta/transfer_learning/textgeneration/v1.0.6/sourcedir.tar.gz",
+        "training_ecr_specs": {
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+        "training_artifact_key": "meta-training/train-meta-textgeneration-llama-2-7b-f.tar.gz",
+        "inference_environment_variables": [],
         "metrics": [
-            {"Name": "huggingface-text2text:eval-loss", "Regex": "'eval_loss': ([0-9\\.]+)"}
-        ],
-        "default_inference_instance_type": "ml.g5.xlarge",
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-            "ml.g5.xlarge",
-            "ml.p2.xlarge",
-            "ml.g4dn.xlarge",
-            "ml.p3.2xlarge",
+            {
+                "Name": "huggingface-textgeneration:eval-loss",
+                "Regex": "eval_epoch_loss=tensor\\(([0-9\\.]+)",
+            },
+            {
+                "Name": "huggingface-textgeneration:eval-ppl",
+                "Regex": "eval_ppl=tensor\\(([0-9\\.]+)",
+            },
+            {
+                "Name": "huggingface-textgeneration:train-loss",
+                "Regex": "train_epoch_loss=([0-9\\.]+)",
+            },
         ],
-        "default_training_instance_type": "ml.p3.16xlarge",
+        "default_inference_instance_type": "ml.g5.2xlarge",
+        "supported_inference_instance_types": [
+            "ml.g5.2xlarge",
+            "ml.g5.4xlarge",
+            "ml.g5.8xlarge",
+            "ml.g5.12xlarge",
+            "ml.g5.24xlarge",
+            "ml.g5.48xlarge",
+            "ml.p4d.24xlarge",
+        ],
+        "default_training_instance_type": "ml.g5.12xlarge",
         "supported_training_instance_types": [
-            "ml.p3.8xlarge",
-            "ml.p3.16xlarge",
-            "ml.p3dn.24xlarge",
+            "ml.g5.12xlarge",
             "ml.g5.24xlarge",
             "ml.g5.48xlarge",
+            "ml.p3dn.24xlarge",
         ],
         "model_kwargs": {},
-        "deploy_kwargs": {},
-        "estimator_kwargs": {"encrypt_inter_container_traffic": False},
+        "deploy_kwargs": {
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+            "container_startup_health_check_timeout": 3600,
+        },
+        "estimator_kwargs": {"encrypt_inter_container_traffic": True, "max_run": 360000},
         "fit_kwargs": {},
         "predictor_specs": {
-            "supported_content_types": ["application/x-text"],
-            "supported_accept_types": ["application/json;verbose", "application/json"],
-            "default_content_type": "application/x-text",
+            "supported_content_types": ["application/json"],
+            "supported_accept_types": ["application/json"],
+            "default_content_type": "application/json",
             "default_accept_type": "application/json",
         },
+        "inference_volume_size": 256,
+        "training_volume_size": 256,
+        "inference_enable_network_isolation": True,
+        "training_enable_network_isolation": True,
+        "default_training_dataset_key": "training-datasets/oasst_top/train/",
+        "validation_supported": True,
+        "fine_tuning_supported": True,
+        "resource_name_base": "meta-textgeneration-llama-2-7b-f",
+        "default_payloads": {
+            "Mayo": {
+                "content_type": "application/json",
+                "body": {
+                    "inputs": [[{"role": "user", "content": "what is the recipe of mayonnaise?"}]],
+                    "parameters": {"max_new_tokens": 512, "top_p": 0.9, "temperature": 0.6},
+                },
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+        },
+        "gated_bucket": True,
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                 "options": ["True", "False"],
                 "scope": "algorithm",
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             {
-                "name": "add_input_output_demarcation_key",
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-                "name": "max_train_samples",
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                 "scope": "algorithm",
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             {
-                "name": "seed",
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                 "scope": "algorithm",
             },
             {
-                "name": "max_input_length",
-                "type": "int",
-                "default": -1,
-                "min": -1,
+                "name": "gradient_checkpointing",
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+                "default": "True",
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                 "scope": "algorithm",
             },
             {
-                "name": "validation_split_ratio",
-                "type": "float",
-                "default": 0.2,
-                "min": 0,
-                "max": 1,
+                "name": "auto_find_batch_size",
+                "type": "text",
+                "default": "False",
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                 "scope": "algorithm",
             },
             {
-                "name": "train_data_split_seed",
-                "type": "int",
-                "default": 0,
-                "min": 0,
+                "name": "preprocessing_num_workers",
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                 "scope": "algorithm",
             },
             {
-                "name": "preprocessing_num_workers",
+                "name": "peft_type",
                 "type": "text",
-                "default": "None",
+                "default": "none",
+                "options": ["lora", "none"],
                 "scope": "algorithm",
             },
             {
@@ -5322,17 +6077,16 @@
                 "scope": "container",
             },
         ],
-        "training_script_key": "source-directory-tarballs/"
-        "meta/transfer_learning/textgeneration/v1.0.4/sourcedir.tar.gz",
-        "training_prepacked_script_key": "source-directory-"
-        "tarballs/meta/transfer_learning/textgeneration/prepack/v1.0.1/sourcedir.tar.gz",
-        "training_prepacked_script_version": "1.0.1",
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+        "training_prepacked_script_key": "source-directory-tarballs/huggingface/transfer_learning/text2text/prepack/v2.0.0/sourcedir.tar.gz",
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         "training_ecr_specs": {
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             "framework_version": "2.0.0",
             "py_version": "py310",
             "huggingface_transformers_version": "4.28.1",
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         "inference_environment_variables": [
             {
                 "name": "SAGEMAKER_PROGRAM",
@@ -5391,23 +6145,23 @@
                 "required_for_model_class": True,
             },
             {
-                "name": "MAX_INPUT_LENGTH",
+                "name": "SM_NUM_GPUS",
                 "type": "text",
-                "default": "4095",
+                "default": "1",
                 "scope": "container",
                 "required_for_model_class": True,
             },
             {
-                "name": "MAX_TOTAL_TOKENS",
+                "name": "MAX_INPUT_LENGTH",
                 "type": "text",
-                "default": "4096",
+                "default": "1024",
                 "scope": "container",
                 "required_for_model_class": True,
             },
             {
-                "name": "SM_NUM_GPUS",
+                "name": "MAX_TOTAL_TOKENS",
                 "type": "text",
-                "default": "1",
+                "default": "2048",
                 "scope": "container",
                 "required_for_model_class": True,
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@@ -5420,42 +6174,33 @@
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         "metrics": [
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-                "Regex": "eval_epoch_loss=tensor\\(([0-9\\.]+)",
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-                "Name": "huggingface-textgeneration:eval-ppl",
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-            },
-            {
-                "Name": "huggingface-textgeneration:train-loss",
-                "Regex": "train_epoch_loss=([0-9\\.]+)",
-            },
+            {"Name": "huggingface-text2text:eval-loss", "Regex": "'eval_loss': ([0-9\\.]+)"}
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             "ml.g5.4xlarge",
             "ml.g5.8xlarge",
-            "ml.g5.12xlarge",
-            "ml.g5.24xlarge",
-            "ml.g5.48xlarge",
-            "ml.p4d.24xlarge",
+            "ml.g5.16xlarge",
         ],
-        "default_training_instance_type": "ml.g5.12xlarge",
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         "supported_training_instance_types": [
-            "ml.g5.12xlarge",
+            "ml.p3.8xlarge",
+            "ml.p3.16xlarge",
+            "ml.p3dn.24xlarge",
             "ml.g5.24xlarge",
             "ml.g5.48xlarge",
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             "container_startup_health_check_timeout": 1200,
         },
-        "estimator_kwargs": {"encrypt_inter_container_traffic": True, "max_run": 360000},
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+            "max_run": 360000,
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         "fit_kwargs": {},
         "predictor_specs": {
             "supported_content_types": ["application/json"],
@@ -5463,83 +6208,127 @@
             "default_content_type": "application/json",
             "default_accept_type": "application/json",
         },
-        "inference_volume_size": 256,
-        "training_volume_size": 256,
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         "inference_enable_network_isolation": True,
         "training_enable_network_isolation": True,
-        "default_training_dataset_key": "training-datasets/sec_amazon/",
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         "validation_supported": True,
         "fine_tuning_supported": True,
-        "resource_name_base": "meta-textgeneration-llama-2-7b",
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-                    "parameters": {"max_new_tokens": 64, "top_p": 0.9, "temperature": 0.6},
-                },
-            },
-            "theoryOfRelativity": {
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                 "content_type": "application/json",
                 "prompt_key": "inputs",
-                "output_keys": {"generated_text": "[0].generated_text"},
-                "body": {
-                    "inputs": "Simply put, the theory of relativity states that ",
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-                "body": {
-                    "inputs": "Translate English to French:\nsea o"
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-                    "input_logprobs": "[0].details.prefill[*].logprob",
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                 "body": {
-                    "inputs": "Please tell me a story.",
+                    "inputs": "Summarize this content - Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document. Use Amazon Comprehend to create new products based on understanding the structure of documents. For example, using Amazon Comprehend you can search social networking feeds for mentions of products or scan an entire document repository for key phrases. You can access Amazon Comprehend document analysis capabilities using the Amazon Comprehend console or using the Amazon Co",
                     "parameters": {
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-                        "top_p": 0.9,
-                        "temperature": 0.2,
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                         "decoder_input_details": True,
                         "details": True,
                     },
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-        "hosting_prepacked_artifact_key": "stabilityai-infer/prepack/v1.0.0/"
-        "infer-prepack-model-depth2img-stable-diffusion-v1-5-controlnet-v1-1-fp16.tar.gz",
+        "hosting_artifact_key": "huggingface-infer/infer-huggingface-text2text-flan-t5-xxl-fp16.tar.gz",
+        "hosting_script_key": "source-directory-tarballs/huggingface/inference/text2text/v1.0.2/sourcedir.tar.gz",
+        "hosting_prepacked_artifact_key": "huggingface-infer/prepack/v1.0.0/infer-prepack-huggingface-"
+        "text2text-flan-t5-xxl-fp16.tar.gz",
         "hosting_prepacked_artifact_version": "1.0.0",
         "inference_vulnerable": False,
         "inference_dependencies": [
-            "accelerate==0.18.0",
-            "diffusers==0.14.0",
-            "fsspec==2023.4.0",
-            "huggingface-hub==0.14.1",
-            "transformers==4.26.1",
+            "accelerate==0.16.0",
+            "bitsandbytes==0.37.0",
+            "filelock==3.9.0",
+            "huggingface-hub==0.12.0",
+            "regex==2022.7.9",
+            "tokenizers==0.13.2",
+            "transformers==4.26.0",
         ],
         "inference_vulnerabilities": [],
         "training_vulnerable": False,
@@ -6566,163 +10679,135 @@
                 "type": "text",
                 "default": "inference.py",
                 "scope": "container",
-                "required_for_model_class": True,
             },
             {
                 "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                 "type": "text",
                 "default": "/opt/ml/model/code",
                 "scope": "container",
-                "required_for_model_class": False,
             },
             {
                 "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                 "type": "text",
                 "default": "20",
                 "scope": "container",
-                "required_for_model_class": False,
-            },
-            {
-                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
-                "type": "text",
-                "default": "3600",
-                "scope": "container",
-                "required_for_model_class": False,
-            },
-            {
-                "name": "ENDPOINT_SERVER_TIMEOUT",
-                "type": "int",
-                "default": 3600,
-                "scope": "container",
-                "required_for_model_class": True,
             },
             {
                 "name": "MODEL_CACHE_ROOT",
                 "type": "text",
                 "default": "/opt/ml/model",
                 "scope": "container",
-                "required_for_model_class": True,
             },
+            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
             {
-                "name": "SAGEMAKER_ENV",
+                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                 "type": "text",
                 "default": "1",
                 "scope": "container",
-                "required_for_model_class": True,
             },
             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
-                "type": "int",
-                "default": 1,
+                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
+                "type": "text",
+                "default": "3600",
                 "scope": "container",
-                "required_for_model_class": True,
             },
         ],
+        "inference_vulnerable": False,
+        "training_vulnerable": False,
+        "deprecated": False,
+        "default_training_instance_type": None,
+        "supported_training_instance_types": [],
         "metrics": [],
-        "default_inference_instance_type": "ml.g5.8xlarge",
+        "default_inference_instance_type": "ml.g5.12xlarge",
         "supported_inference_instance_types": [
-            "ml.g5.8xlarge",
-            "ml.g5.xlarge",
-            "ml.g5.2xlarge",
-            "ml.g5.4xlarge",
-            "ml.g5.16xlarge",
-            "ml.p3.2xlarge",
-            "ml.g4dn.xlarge",
-            "ml.g4dn.2xlarge",
-            "ml.g4dn.4xlarge",
-            "ml.g4dn.8xlarge",
-            "ml.g4dn.16xlarge",
+            "ml.g5.12xlarge",
+            "ml.g5.24xlarge",
+            "ml.p3.8xlarge",
+            "ml.p3.16xlarge",
+            "ml.g4dn.12xlarge",
         ],
-        "model_kwargs": {},
-        "deploy_kwargs": {},
-        "predictor_specs": {
-            "supported_content_types": ["application/json"],
-            "supported_accept_types": ["application/json"],
-            "default_content_type": "application/json",
-            "default_accept_type": "application/json",
-        },
-        "inference_enable_network_isolation": True,
-        "validation_supported": False,
-        "fine_tuning_supported": False,
-        "resource_name_base": "sd-1-5-controlnet-1-1-fp16",
-        "default_payloads": {
-            "Dog": {
-                "content_type": "application/json",
-                "prompt_key": "hello.prompt",
-                "body": {
-                    "hello": {"prompt": "a dog"},
-                    "seed": 43,
-                },
-            }
-        },
-        "hosting_instance_type_variants": {
-            "regional_aliases": {
-                "af-south-1": {
-                    "alias_ecr_uri_1": "626614931356.dkr.ecr.af-south-1.amazonaws.com/d"
-                    "jl-inference:0.21.0-deepspeed0.8.3-cu117"
-                },
-            },
-            "variants": {
-                "c4": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "c5": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "c5d": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "c5n": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "c6i": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "g4dn": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "g5": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "inf1": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "inf2": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "local": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "local_gpu": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "m4": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "m5": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "m5d": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "p2": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "p3": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "p3dn": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "p4d": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "p4de": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "p5": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "r5": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "r5d": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "t2": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-                "t3": {"regional_properties": {"image_uri": "$alias_ecr_uri_1"}},
-            },
-        },
     },
-    "predictor-specs-model": {
-        "model_id": "huggingface-text2text-flan-t5-xxl-fp16",
-        "url": "https://huggingface.co/google/flan-t5-xxl",
-        "version": "1.0.1",
-        "min_sdk_version": "2.130.0",
-        "training_supported": False,
+    "mock-model-training-prepacked-script-key": {
+        "model_id": "sklearn-classification-linear",
+        "url": "https://scikit-learn.org/stable/",
+        "version": "1.0.0",
+        "min_sdk_version": "2.68.1",
+        "training_supported": True,
         "incremental_training_supported": False,
         "hosting_ecr_specs": {
-            "framework": "pytorch",
-            "framework_version": "1.12.0",
-            "py_version": "py38",
-            "huggingface_transformers_version": "4.17.0",
+            "framework": "sklearn",
+            "framework_version": "0.23-1",
+            "py_version": "py3",
         },
-        "hosting_artifact_key": "huggingface-infer/infer-huggingface-text2text-flan-t5-xxl-fp16.tar.gz",
-        "hosting_script_key": "source-directory-tarballs/huggingface/inference/text2text/v1.0.3/sourcedir.tar.gz",
-        "hosting_prepacked_artifact_key": "huggingface-infer/prepack/v1.0.1/infer-prepack-huggingface-"
-        "text2text-flan-t5-xxl-fp16.tar.gz",
-        "hosting_prepacked_artifact_version": "1.0.1",
+        "hosting_artifact_key": "sklearn-infer/infer-sklearn-classification-linear.tar.gz",
+        "hosting_script_key": "source-directory-tarballs/sklearn/inference/classification/v1.0.0/sourcedir.tar.gz",
         "inference_vulnerable": False,
-        "inference_dependencies": [
-            "accelerate==0.16.0",
-            "bitsandbytes==0.37.0",
-            "filelock==3.9.0",
-            "huggingface_hub==0.12.0",
-            "regex==2022.7.9",
-            "tokenizers==0.13.2",
-            "transformers==4.26.0",
+        "inference_dependencies": [],
+        "inference_vulnerabilities": [],
+        "training_vulnerable": False,
+        "training_dependencies": [],
+        "training_vulnerabilities": [],
+        "deprecated": False,
+        "hyperparameters": [
+            {
+                "name": "tol",
+                "type": "float",
+                "default": 0.0001,
+                "min": 1e-20,
+                "max": 50,
+                "scope": "algorithm",
+            },
+            {
+                "name": "penalty",
+                "type": "text",
+                "default": "l2",
+                "options": ["l1", "l2", "elasticnet", "none"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "alpha",
+                "type": "float",
+                "default": 0.0001,
+                "min": 1e-20,
+                "max": 999,
+                "scope": "algorithm",
+            },
+            {
+                "name": "l1_ratio",
+                "type": "float",
+                "default": 0.15,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "sagemaker_submit_directory",
+                "type": "text",
+                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
+                "scope": "container",
+            },
+            {
+                "name": "sagemaker_program",
+                "type": "text",
+                "default": "transfer_learning.py",
+                "scope": "container",
+            },
+            {
+                "name": "sagemaker_container_log_level",
+                "type": "text",
+                "default": "20",
+                "scope": "container",
+            },
         ],
-        "inference_vulnerabilities": [],
-        "training_vulnerable": False,
-        "training_dependencies": [],
-        "training_vulnerabilities": [],
-        "deprecated": False,
+        "training_script_key": "source-directory-tarballs/sklearn/transfer_learning/classification/"
+        "v1.0.0/sourcedir.tar.gz",
+        "training_prepacked_script_key": "some/key/to/training_prepacked_script_key.tar.gz",
+        "training_ecr_specs": {
+            "framework_version": "0.23-1",
+            "framework": "sklearn",
+            "py_version": "py3",
+        },
+        "training_artifact_key": "sklearn-training/train-sklearn-classification-linear.tar.gz",
         "inference_environment_variables": [
             {
                 "name": "SAGEMAKER_PROGRAM",
@@ -6762,364 +10847,772 @@
                 "scope": "container",
             },
         ],
-        "metrics": [],
-        "default_inference_instance_type": "ml.g5.12xlarge",
-        "supported_inference_instance_types": [
-            "ml.g5.12xlarge",
-            "ml.g5.24xlarge",
-            "ml.p3.8xlarge",
-            "ml.p3.16xlarge",
-            "ml.g4dn.12xlarge",
-        ],
-        "predictor_specs": {
-            "supported_content_types": ["application/x-text"],
-            "supported_accept_types": ["application/json;verbose", "application/json"],
-            "default_content_type": "application/x-text",
-            "default_accept_type": "application/json",
-        },
     },
-    "model_data_s3_prefix_model": {
-        "model_id": "huggingface-text2text-flan-t5-xxl-fp16",
-        "url": "https://huggingface.co/google/flan-t5-xxl",
-        "version": "1.0.1",
-        "min_sdk_version": "2.130.0",
-        "training_supported": False,
-        "incremental_training_supported": False,
+}
+
+
+PROTOTYPICAL_MODEL_SPECS_DICT = {
+    "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1": {
+        "model_id": "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1",
+        "url": "https://tfhub.dev/google/bit/m-r101x1/ilsvrc2012_classification/1",
+        "version": "4.0.6",
+        "min_sdk_version": "2.189.0",
+        "training_supported": True,
+        "incremental_training_supported": True,
         "hosting_ecr_specs": {
-            "framework": "pytorch",
-            "framework_version": "1.12.0",
-            "py_version": "py38",
-            "huggingface_transformers_version": "4.17.0",
+            "framework": "tensorflow",
+            "framework_version": "2.8",
+            "py_version": "py39",
         },
-        "hosting_artifact_key": "huggingface-infer/",
-        "hosting_script_key": "source-directory-tarballs/huggingface/inference/text2text/v1.0.3/sourcedir.tar.gz",
-        "hosting_prepacked_artifact_key": "huggingface-infer/prepack/v1.0.1/",
-        "hosting_prepacked_artifact_version": "1.0.1",
+        "hosting_artifact_key": "tensorflow-ic/tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1/artifacts/inference/v3.0.0/",
+        "hosting_script_key": "source-directory-tarballs/tensorflow/inference/ic/v2.0.3/sourcedir.tar.gz",
+        "hosting_prepacked_artifact_key": "tensorflow-ic/tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1/artifacts/inference-prepack/v1.0.0/",
+        "hosting_prepacked_artifact_version": "1.0.0",
+        "hosting_use_script_uri": False,
         "inference_vulnerable": False,
-        "inference_dependencies": [
-            "accelerate==0.16.0",
-            "bitsandbytes==0.37.0",
-            "filelock==3.9.0",
-            "huggingface_hub==0.12.0",
-            "regex==2022.7.9",
-            "tokenizers==0.13.2",
-            "transformers==4.26.0",
+        "inference_dependencies": [],
+        "inference_vulnerabilities": [],
+        "training_vulnerable": False,
+        "training_dependencies": [
+            "sagemaker_jumpstart_prepack_script_utilities==1.0.0",
+            "sagemaker_jumpstart_script_utilities==1.1.1",
+            "sagemaker_jumpstart_tensorflow_script_utilities==1.0.1",
+        ],
+        "training_vulnerabilities": [],
+        "deprecated": False,
+        "hyperparameters": [
+            {
+                "name": "train_only_top_layer",
+                "type": "text",
+                "default": "True",
+                "options": ["False", "True"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "epochs",
+                "type": "int",
+                "default": 5,
+                "min": 1,
+                "max": 1000,
+                "scope": "algorithm",
+            },
+            {
+                "name": "batch_size",
+                "type": "int",
+                "default": 32,
+                "min": 1,
+                "max": 1024,
+                "scope": "algorithm",
+            },
+            {
+                "name": "optimizer",
+                "type": "text",
+                "default": "adam",
+                "options": ["adam", "sgd", "nesterov", "rmsprop", "adagrad", "adadelta"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "learning_rate",
+                "type": "float",
+                "default": 0.001,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "beta_1",
+                "type": "float",
+                "default": 0.9,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "beta_2",
+                "type": "float",
+                "default": 0.999,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "momentum",
+                "type": "float",
+                "default": 0.9,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "epsilon",
+                "type": "float",
+                "default": 1e-07,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "rho",
+                "type": "float",
+                "default": 0.95,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "initial_accumulator_value",
+                "type": "float",
+                "default": 0.1,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "reinitialize_top_layer",
+                "type": "text",
+                "default": "Auto",
+                "options": ["Auto", "True", "False"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "early_stopping",
+                "type": "text",
+                "default": "False",
+                "options": ["False", "True"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "early_stopping_patience",
+                "type": "int",
+                "default": 5,
+                "min": 1,
+                "max": 1000,
+                "scope": "algorithm",
+            },
+            {
+                "name": "early_stopping_min_delta",
+                "type": "float",
+                "default": 0.0,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "dropout_rate",
+                "type": "float",
+                "default": 0.2,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "regularizers_l2",
+                "type": "float",
+                "default": 0.0001,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "label_smoothing",
+                "type": "float",
+                "default": 0.1,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "image_resize_interpolation",
+                "type": "text",
+                "default": "bilinear",
+                "options": [
+                    "bilinear",
+                    "nearest",
+                    "bicubic",
+                    "area",
+                    "lanczos3",
+                    "lanczos5",
+                    "gaussian",
+                    "mitchellcubic",
+                ],
+                "scope": "algorithm",
+            },
+            {
+                "name": "augmentation",
+                "type": "text",
+                "default": "False",
+                "options": ["False", "True"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "augmentation_random_flip",
+                "type": "text",
+                "default": "horizontal_and_vertical",
+                "options": ["horizontal_and_vertical", "horizontal", "vertical", "None"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "augmentation_random_rotation",
+                "type": "float",
+                "default": 0.2,
+                "min": -1,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "augmentation_random_zoom",
+                "type": "float",
+                "default": 0.1,
+                "min": -1,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "binary_mode",
+                "type": "text",
+                "default": "False",
+                "options": ["False", "True"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "eval_metric",
+                "type": "text",
+                "default": "accuracy",
+                "options": ["accuracy", "precision", "recall", "auc", "prc"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "validation_split_ratio",
+                "type": "float",
+                "default": 0.2,
+                "min": 0,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {"name": "random_seed", "type": "int", "default": 123, "min": 0, "scope": "algorithm"},
+            {
+                "name": "sagemaker_submit_directory",
+                "type": "text",
+                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
+                "scope": "container",
+            },
+            {
+                "name": "sagemaker_program",
+                "type": "text",
+                "default": "transfer_learning.py",
+                "scope": "container",
+            },
+            {
+                "name": "sagemaker_container_log_level",
+                "type": "text",
+                "default": "20",
+                "scope": "container",
+            },
         ],
-        "inference_vulnerabilities": [],
-        "training_vulnerable": False,
-        "training_dependencies": [],
-        "training_vulnerabilities": [],
-        "deprecated": False,
+        "training_script_key": "source-directory-tarballs/tensorflow/transfer_learning/ic/v2.1.2/sourcedir.tar.gz",
+        "training_prepacked_script_key": "source-directory-tarballs/tensorflow/transfer_learning/ic/prepack/v1.1.2/sourcedir.tar.gz",
+        "training_prepacked_script_version": "1.1.2",
+        "training_ecr_specs": {
+            "framework": "tensorflow",
+            "framework_version": "2.9",
+            "py_version": "py39",
+        },
+        "training_artifact_key": "tensorflow-training/v3.0.0/train-tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1.tar.gz",
         "inference_environment_variables": [
             {
                 "name": "SAGEMAKER_PROGRAM",
                 "type": "text",
                 "default": "inference.py",
                 "scope": "container",
+                "required_for_model_class": True,
             },
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+        "hosting_artifact_compression_type": "None",
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-
-
-PROTOTYPICAL_MODEL_SPECS_DICT = {
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+        "url": "https://cv.gluon.ai/model_zoo/segmentation.html",
+        "version": "2.0.3",
+        "min_sdk_version": "2.189.0",
         "training_supported": True,
-        "incremental_training_supported": False,
+        "incremental_training_supported": True,
         "hosting_ecr_specs": {
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-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework": "mxnet",
+            "framework_version": "1.9.0",
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         },
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-        "supported_inference_instance_type": ["ml.p2.xlarge", "ml.p3.xlarge"],
-        "default_training_instance_type": "ml.p2.xlarge",
-        "supported_training_instance_type": ["ml.p2.xlarge", "ml.p3.xlarge"],
-        "hosting_artifact_key": "pytorch-infer/infer-pytorch-eqa-bert-base-cased.tar.gz",
-        "hosting_script_key": "source-directory-tarballs/pytorch/inference/eqa/v1.0.0/sourcedir.tar.gz",
+        "hosting_artifact_key": "mxnet-semseg/mxnet-semseg-fcn-resnet50-ade/artifacts/inference/v1.1.0/",
+        "hosting_script_key": "source-directory-tarballs/mxnet/inference/semseg/v1.2.1/sourcedir.tar.gz",
+        "hosting_prepacked_artifact_key": "mxnet-semseg/mxnet-semseg-fcn-resnet50-ade/artifacts/inference-prepack/v1.0.0/",
+        "hosting_prepacked_artifact_version": "1.0.0",
+        "hosting_use_script_uri": False,
         "inference_vulnerable": False,
-        "inference_dependencies": [
-            "transformers==3.5.1",
-            "dataclasses==0.8",
-            "filelock==3.0.12",
-            "packaging==20.8",
-            "pyparsing==2.4.7",
-            "regex==2020.11.13",
-            "sacremoses==0.0.43",
-            "sentencepiece==0.1.91",
-            "tokenizers==0.9.3",
-        ],
+        "inference_dependencies": [],
         "inference_vulnerabilities": [],
         "training_vulnerable": False,
         "training_dependencies": [
-            "transformers==3.5.1",
-            "dataclasses==0.8",
-            "filelock==3.0.12",
-            "packaging==20.8",
-            "pyparsing==2.4.7",
-            "regex==2020.11.13",
-            "sacremoses==0.0.43",
-            "sentencepiece==0.1.91",
-            "tokenizers==0.9.3",
+            "numpy==1.23.1",
+            "opencv_python==4.7.0.68",
+            "sagemaker_jumpstart_prepack_script_utilities==1.0.0",
         ],
         "training_vulnerabilities": [],
         "deprecated": False,
@@ -7243,7 +12105,7 @@
             {
                 "name": "epochs",
                 "type": "int",
-                "default": 3,
+                "default": 5,
                 "min": 1,
                 "max": 1000,
                 "scope": "algorithm",
@@ -7251,7 +12113,7 @@
             {
                 "name": "adam-learning-rate",
                 "type": "float",
-                "default": 2e-05,
+                "default": 0.001,
                 "min": 1e-08,
                 "max": 1,
                 "scope": "algorithm",
@@ -7259,11 +12121,18 @@
             {
                 "name": "batch-size",
                 "type": "int",
-                "default": 4,
+                "default": 2,
                 "min": 1,
                 "max": 1024,
                 "scope": "algorithm",
             },
+            {
+                "name": "train-only-top-layer",
+                "type": "text",
+                "default": "True",
+                "options": ["True", "False"],
+                "scope": "algorithm",
+            },
             {
                 "name": "sagemaker_submit_directory",
                 "type": "text",
@@ -7283,78 +12152,447 @@
                 "scope": "container",
             },
         ],
-        "training_script_key": "source-directory-tarballs/pytorch/transfer_learning/eqa/v1.0.0/sourcedir.tar.gz",
+        "training_script_key": "source-directory-tarballs/mxnet/transfer_learning/semseg/v1.5.0/sourcedir.tar.gz",
+        "training_prepacked_script_key": "source-directory-tarballs/mxnet/transfer_learning/semseg/prepack/v1.1.0/sourcedir.tar.gz",
+        "training_prepacked_script_version": "1.1.0",
         "training_ecr_specs": {
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-            "framework": "pytorch",
-            "py_version": "py3",
-        },
-        "training_artifact_key": "pytorch-training/train-pytorch-eqa-bert-base-cased.tar.gz",
-        "predictor_specs": {
-            "supported_content_types": ["application/x-image"],
-            "supported_accept_types": ["application/json;verbose", "application/json"],
-            "default_content_type": "application/x-image",
-            "default_accept_type": "application/json",
+            "framework": "mxnet",
+            "framework_version": "1.9.0",
+            "py_version": "py38",
         },
+        "training_artifact_key": "mxnet-training/train-mxnet-semseg-fcn-resnet50-ade.tar.gz",
         "inference_environment_variables": [
             {
                 "name": "SAGEMAKER_PROGRAM",
                 "type": "text",
                 "default": "inference.py",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                 "type": "text",
                 "default": "/opt/ml/model/code",
                 "scope": "container",
+                "required_for_model_class": False,
             },
             {
                 "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                 "type": "text",
                 "default": "20",
                 "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
+                "type": "text",
+                "default": "3600",
+                "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "ENDPOINT_SERVER_TIMEOUT",
+                "type": "int",
+                "default": 3600,
+                "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "MODEL_CACHE_ROOT",
                 "type": "text",
                 "default": "/opt/ml/model",
                 "scope": "container",
+                "required_for_model_class": True,
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-            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "name": "SAGEMAKER_ENV",
                 "type": "text",
                 "default": "1",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
-                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
-                "type": "text",
-                "default": "3600",
+                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "type": "int",
+                "default": 1,
                 "scope": "container",
+                "required_for_model_class": True,
             },
         ],
+        "metrics": [{"Name": "mxnet-semseg:val-loss", "Regex": "validation loss=([0-9\\.]+)"}],
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+        "supported_inference_instance_types": [
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+            "ml.p3.2xlarge",
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+            "ml.p3.8xlarge",
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+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
+            "ml.c5.9xlarge",
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+        },
+        "inference_enable_network_isolation": True,
+        "training_enable_network_isolation": True,
+        "default_training_dataset_key": "training-datasets/PennFudanPed_SemSeg/",
+        "validation_supported": False,
+        "fine_tuning_supported": True,
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@@ -7377,11 +12615,25 @@
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             },
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+            {"name": "max_bin", "type": "int", "default": 255, "min": 2, "scope": "algorithm"},
+            {"name": "num_threads", "type": "int", "default": 0, "min": 0, "scope": "algorithm"},
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             {
@@ -7786,11 +13210,12 @@
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@@ -7800,74 +13225,501 @@
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             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
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             {
-                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
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-            "scikit_learn==1.0.1",
-            "threadpoolctl==2.2.0",
+            "catboost==1.2.2",
+            "graphviz==0.20.1",
+            "plotly==5.18.0",
+            "tenacity==8.2.3",
         ],
         "inference_vulnerabilities": [],
         "training_vulnerable": False,
         "training_dependencies": [
-            "tenacity==8.0.1",
-            "plotly==5.1.0",
-            "graphviz==0.17",
             "catboost==1.0.1",
+            "graphviz==0.17",
+            "plotly==5.1.0",
+            "sagemaker_jumpstart_prepack_script_utilities==1.0.0",
+            "sagemaker_jumpstart_script_utilities==1.0.1",
+            "tenacity==8.0.1",
         ],
         "training_vulnerabilities": [],
         "deprecated": False,
@@ -7888,6 +13740,7 @@
                 "max": 5000,
                 "scope": "algorithm",
             },
+            {"name": "eval_metric", "type": "text", "default": "Auto", "scope": "algorithm"},
             {
                 "name": "learning_rate",
                 "type": "float",
@@ -7920,6 +13773,61 @@
                 "max": 10,
                 "scope": "algorithm",
             },
+            {"name": "max_leaves", "type": "int", "default": 31, "min": 2, "scope": "algorithm"},
+            {
+                "name": "rsm",
+                "type": "float",
+                "default": 1,
+                "min": 1e-20,
+                "max": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "sampling_frequency",
+                "type": "text",
+                "default": "PerTreeLevel",
+                "options": ["PerTreeLevel", "PerTree"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "min_data_in_leaf",
+                "type": "int",
+                "default": 1,
+                "min": 1,
+                "scope": "algorithm",
+            },
+            {
+                "name": "bagging_temperature",
+                "type": "float",
+                "default": 1,
+                "min": 0,
+                "scope": "algorithm",
+            },
+            {
+                "name": "boosting_type",
+                "type": "text",
+                "default": "Auto",
+                "options": ["Auto", "Ordered", "Plain"],
+                "scope": "algorithm",
+            },
+            {
+                "name": "scale_pos_weight",
+                "type": "float",
+                "default": 1.0,
+                "min": 1e-20,
+                "scope": "algorithm",
+            },
+            {"name": "max_bin", "type": "text", "default": "Auto", "scope": "algorithm"},
+            {
+                "name": "grow_policy",
+                "type": "text",
+                "default": "SymmetricTree",
+                "options": ["SymmetricTree", "Depthwise", "Lossguide"],
+                "scope": "algorithm",
+            },
+            {"name": "random_seed", "type": "int", "default": 0, "min": 0, "scope": "algorithm"},
+            {"name": "thread_count", "type": "int", "default": -1, "min": -1, "scope": "algorithm"},
+            {"name": "verbose", "type": "int", "default": 1, "min": 1, "scope": "algorithm"},
             {
                 "name": "sagemaker_submit_directory",
                 "type": "text",
@@ -7939,11 +13847,12 @@
                 "scope": "container",
             },
         ],
-        "training_script_key": "source-directory-tarballs/catboost/transfer_learning/"
-        "classification/v1.0.0/sourcedir.tar.gz",
+        "training_script_key": "source-directory-tarballs/catboost/transfer_learning/classification/v1.2.0/sourcedir.tar.gz",
+        "training_prepacked_script_key": "source-directory-tarballs/catboost/transfer_learning/classification/prepack/v1.1.1/sourcedir.tar.gz",
+        "training_prepacked_script_version": "1.1.1",
         "training_ecr_specs": {
-            "framework_version": "1.9.0",
             "framework": "pytorch",
+            "framework_version": "1.9.0",
             "py_version": "py38",
         },
         "training_artifact_key": "catboost-training/train-catboost-classification-model.tar.gz",
@@ -7953,59 +13862,538 @@
                 "type": "text",
                 "default": "inference.py",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                 "type": "text",
                 "default": "/opt/ml/model/code",
                 "scope": "container",
+                "required_for_model_class": False,
             },
             {
                 "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                 "type": "text",
                 "default": "20",
                 "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
+                "type": "text",
+                "default": "3600",
+                "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "ENDPOINT_SERVER_TIMEOUT",
+                "type": "int",
+                "default": 3600,
+                "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "MODEL_CACHE_ROOT",
                 "type": "text",
                 "default": "/opt/ml/model",
                 "scope": "container",
+                "required_for_model_class": True,
             },
-            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "name": "SAGEMAKER_ENV",
                 "type": "text",
                 "default": "1",
                 "scope": "container",
+                "required_for_model_class": True,
+            },
+            {
+                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "type": "int",
+                "default": 1,
+                "scope": "container",
+                "required_for_model_class": True,
+            },
+        ],
+        "metrics": [
+            {"Name": "catboost-classification:multi-logloss", "Regex": "multi_logloss: ([0-9\\.]+)"}
+        ],
+        "default_inference_instance_type": "ml.m5.4xlarge",
+        "supported_inference_instance_types": [
+            "ml.m5.2xlarge",
+            "ml.m5.4xlarge",
+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
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+            "ml.c5.4xlarge",
+            "ml.c5.9xlarge",
+            "ml.c5.18xlarge",
+            "ml.m4.16xlarge",
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+        "supported_training_instance_types": [
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+            "ml.m5.2xlarge",
+            "ml.m5.4xlarge",
+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
+            "ml.c5.2xlarge",
+            "ml.c5.4xlarge",
+            "ml.c5.9xlarge",
+            "ml.c5.18xlarge",
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+        "default_training_dataset_key": "training-datasets/tabular_multiclass/",
+        "validation_supported": True,
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+            "platformdirs==3.8.0",
+            "pox==0.3.2",
+            "ppft==1.7.6.6",
+            "protobuf3-to-dict==0.1.5",
+            "protobuf==3.20.3",
+            "pycparser==2.21",
+            "pycryptodomex==3.12.0",
+            "pyjwt==2.7.0",
+            "pyopenssl==23.2.0",
+            "pyrsistent==0.19.3",
+            "python-dateutil==2.8.2",
+            "pytz==2023.3",
+            "pyyaml==6.0",
+            "requests==2.31.0",
+            "s3transfer==0.6.1",
+            "sagemaker==2.164.0",
+            "sagemaker_jumpstart_script_utilities==1.0.1",
+            "sagemaker_jumpstart_snowflake_script_utilities==1.1.0",
+            "schema==0.7.5",
+            "six==1.16.0",
+            "smdebug-rulesconfig==1.0.1",
+            "snowflake-connector-python==3.12.3",
+            "tblib==1.7.0",
+            "typing-extensions==4.6.3",
+            "tzdata==2023.3",
+            "urllib3==1.26.16",
+            "zipp==3.15.0",
+        ],
         "training_vulnerabilities": [],
         "deprecated": False,
         "hyperparameters": [
@@ -8093,11 +14481,10 @@
                 "scope": "container",
             },
         ],
-        "training_script_key": "source-directory-tarballs/xgboost/transfer_learning/classification/"
-        "v1.0.0/sourcedir.tar.gz",
+        "training_script_key": "source-directory-tarballs/training/xgboost-classification/v1.3.1/sourcedir.tar.gz",
         "training_ecr_specs": {
-            "framework_version": "1.3-1",
             "framework": "xgboost",
+            "framework_version": "1.7-1",
             "py_version": "py3",
         },
         "training_artifact_key": "xgboost-training/train-xgboost-classification-model.tar.gz",
@@ -8107,59 +14494,430 @@
                 "type": "text",
                 "default": "inference.py",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                 "type": "text",
                 "default": "/opt/ml/model/code",
                 "scope": "container",
+                "required_for_model_class": False,
             },
             {
                 "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                 "type": "text",
                 "default": "20",
                 "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
+                "type": "text",
+                "default": "3600",
+                "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "ENDPOINT_SERVER_TIMEOUT",
+                "type": "int",
+                "default": 3600,
+                "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "MODEL_CACHE_ROOT",
                 "type": "text",
                 "default": "/opt/ml/model",
                 "scope": "container",
+                "required_for_model_class": True,
             },
-            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "name": "SAGEMAKER_ENV",
                 "type": "text",
                 "default": "1",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
-                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
-                "type": "text",
-                "default": "3600",
+                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "type": "int",
+                "default": 1,
                 "scope": "container",
+                "required_for_model_class": True,
             },
         ],
+        "metrics": [],
+        "default_inference_instance_type": "ml.m5.xlarge",
+        "supported_inference_instance_types": [
+            "ml.m5.xlarge",
+            "ml.m5.2xlarge",
+            "ml.m5.4xlarge",
+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
+            "ml.c5.2xlarge",
+            "ml.c5.4xlarge",
+            "ml.c5.9xlarge",
+            "ml.c5.18xlarge",
+            "ml.c4.8xlarge",
+        ],
+        "default_training_instance_type": "ml.m5.4xlarge",
+        "supported_training_instance_types": [
+            "ml.m5.xlarge",
+            "ml.m5.2xlarge",
+            "ml.m5.4xlarge",
+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
+            "ml.c5.2xlarge",
+            "ml.c5.4xlarge",
+            "ml.c5.9xlarge",
+            "ml.c5.18xlarge",
+            "ml.c4.8xlarge",
+        ],
+        "model_kwargs": {},
+        "deploy_kwargs": {},
+        "estimator_kwargs": {"encrypt_inter_container_traffic": True, "max_run": 360000},
+        "fit_kwargs": {},
+        "predictor_specs": {
+            "supported_content_types": ["text/csv"],
+            "supported_accept_types": ["application/json", "application/json;verbose"],
+            "default_content_type": "text/csv",
+            "default_accept_type": "application/json",
+        },
+        "inference_enable_network_isolation": True,
+        "training_enable_network_isolation": True,
+        "default_training_dataset_key": "training-datasets/tabular_multiclass/",
+        "validation_supported": True,
+        "fine_tuning_supported": False,
+        "resource_name_base": "xgb-classification-model",
+        "hosting_instance_type_variants": {
+            "regional_aliases": {
+                "af-south-1": {
+                    "xgb_ecr_uri_1": "510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost@sha256:ba417ec6d8d3e0c6b5f463bc9202e3b498b42260a29b61875f34beb6d99d8444"
+                },
+                "ap-east-1": {
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+                },
+                "ap-northeast-1": {
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
+            },
+            "variants": {
+                "c4": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c5d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c5n": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c6i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c6id": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c7i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g4dn": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g6": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g6e": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "inf1": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "inf2": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "local": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "local_gpu": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m4": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m5d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m6i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m6id": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m7i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p2": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p3": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p3dn": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p4d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p4de": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r5d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r6i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r6id": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r7i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "t2": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "t3": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+            },
+        },
+        "training_instance_type_variants": {
+            "regional_aliases": {
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                },
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+                "c5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c5d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c5n": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c6i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c6id": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "c7i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g4dn": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g6": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "g6e": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "inf1": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "inf2": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "local": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "local_gpu": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m4": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m5d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m6i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m6id": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "m7i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p2": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p3": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p3dn": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "p4d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
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+                "p5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r5": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r5d": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
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+                "r6id": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "r7i": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "t2": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+                "t3": {"regional_properties": {"image_uri": "$xgb_ecr_uri_1"}},
+            },
+        },
+        "dynamic_container_deployment_supported": False,
     },
     "sklearn-classification-linear": {
         "model_id": "sklearn-classification-linear",
         "url": "https://scikit-learn.org/stable/",
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-        "min_sdk_version": "2.68.1",
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         "training_supported": True,
         "incremental_training_supported": False,
         "hosting_ecr_specs": {
             "framework": "sklearn",
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             "py_version": "py3",
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         "hosting_artifact_key": "sklearn-infer/infer-sklearn-classification-linear.tar.gz",
-        "hosting_script_key": "source-directory-tarballs/sklearn/inference/classification/v1.0.0/sourcedir.tar.gz",
+        "hosting_script_key": "source-directory-tarballs/sklearn/inference/classification/v1.1.0/sourcedir.tar.gz",
+        "hosting_use_script_uri": True,
         "inference_vulnerable": False,
         "inference_dependencies": [],
         "inference_vulnerabilities": [],
         "training_vulnerable": False,
-        "training_dependencies": [],
+        "training_dependencies": [
+            "asn1crypto==1.5.1",
+            "attrs==23.1.0",
+            "boto3==1.26.158",
+            "botocore==1.29.159",
+            "certifi==2023.5.7",
+            "cffi==1.15.1",
+            "charset-normalizer==2.1.1",
+            "cloudpickle==2.2.1",
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+            "cryptography==40.0.2",
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+            "idna==3.4",
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+            "jmespath==1.0.1",
+            "jsonschema==4.17.3",
+            "multiprocess==0.70.14",
+            "numpy==1.24.3",
+            "oscrypto==1.3.0",
+            "packaging==23.1",
+            "pandas==2.0.2",
+            "pathos==0.3.0",
+            "pkgutil-resolve-name==1.3.10",
+            "platformdirs==3.8.0",
+            "pox==0.3.2",
+            "ppft==1.7.6.6",
+            "protobuf3-to-dict==0.1.5",
+            "protobuf==3.20.3",
+            "pycparser==2.21",
+            "pycryptodomex==3.12.0",
+            "pyjwt==2.7.0",
+            "pyopenssl==23.2.0",
+            "pyrsistent==0.19.3",
+            "python-dateutil==2.8.2",
+            "pytz==2023.3",
+            "pyyaml==6.0",
+            "requests==2.31.0",
+            "s3transfer==0.6.1",
+            "sagemaker==2.164.0",
+            "sagemaker_jumpstart_script_utilities==1.0.1",
+            "sagemaker_jumpstart_snowflake_script_utilities==1.1.0",
+            "schema==0.7.5",
+            "six==1.16.0",
+            "smdebug-rulesconfig==1.0.1",
+            "snowflake-connector-python==3.12.3",
+            "tblib==1.7.0",
+            "typing-extensions==4.6.3",
+            "tzdata==2023.3",
+            "urllib3==1.26.16",
+            "zipp==3.15.0",
+        ],
         "training_vulnerabilities": [],
         "deprecated": False,
         "hyperparameters": [
@@ -8213,11 +14971,10 @@
                 "scope": "container",
             },
         ],
-        "training_script_key": "source-directory-tarballs/sklearn/transfer_learning/classification/"
-        "v1.0.0/sourcedir.tar.gz",
+        "training_script_key": "source-directory-tarballs/training/sklearn-classification/v2.0.1/sourcedir.tar.gz",
         "training_ecr_specs": {
-            "framework_version": "0.23-1",
             "framework": "sklearn",
+            "framework_version": "1.2-1",
             "py_version": "py3",
         },
         "training_artifact_key": "sklearn-training/train-sklearn-classification-linear.tar.gz",
@@ -8227,99 +14984,460 @@
                 "type": "text",
                 "default": "inference.py",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                 "type": "text",
                 "default": "/opt/ml/model/code",
                 "scope": "container",
+                "required_for_model_class": False,
             },
             {
                 "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                 "type": "text",
                 "default": "20",
                 "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
+                "type": "text",
+                "default": "3600",
+                "scope": "container",
+                "required_for_model_class": False,
+            },
+            {
+                "name": "ENDPOINT_SERVER_TIMEOUT",
+                "type": "int",
+                "default": 3600,
+                "scope": "container",
+                "required_for_model_class": True,
             },
             {
                 "name": "MODEL_CACHE_ROOT",
                 "type": "text",
                 "default": "/opt/ml/model",
                 "scope": "container",
+                "required_for_model_class": True,
             },
-            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
             {
-                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "name": "SAGEMAKER_ENV",
                 "type": "text",
                 "default": "1",
                 "scope": "container",
+                "required_for_model_class": True,
             },
             {
-                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
-                "type": "text",
-                "default": "3600",
+                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
+                "type": "int",
+                "default": 1,
                 "scope": "container",
+                "required_for_model_class": True,
             },
         ],
+        "metrics": [],
+        "default_inference_instance_type": "ml.m5.xlarge",
+        "supported_inference_instance_types": [
+            "ml.m5.xlarge",
+            "ml.m5.2xlarge",
+            "ml.m5.4xlarge",
+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
+            "ml.c5.2xlarge",
+            "ml.c5.4xlarge",
+            "ml.c5.9xlarge",
+            "ml.c5.18xlarge",
+            "ml.c4.8xlarge",
+        ],
+        "default_training_instance_type": "ml.m5.4xlarge",
+        "supported_training_instance_types": [
+            "ml.m5.xlarge",
+            "ml.m5.2xlarge",
+            "ml.m5.4xlarge",
+            "ml.m5.12xlarge",
+            "ml.m5.24xlarge",
+            "ml.c5.2xlarge",
+            "ml.c5.4xlarge",
+            "ml.c5.9xlarge",
+            "ml.c5.18xlarge",
+            "ml.c4.8xlarge",
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+        "deploy_kwargs": {},
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+        "training_enable_network_isolation": True,
+        "default_training_dataset_key": "training-datasets/tabular_multiclass/",
+        "validation_supported": True,
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+                "m6g": {"regional_properties": {"image_uri": "$cpu_ecr_uri_2"}},
+                "m6gd": {"regional_properties": {"image_uri": "$cpu_ecr_uri_2"}},
+                "m6i": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "m6id": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "m7i": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "r5": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "r5d": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "r6g": {"regional_properties": {"image_uri": "$cpu_ecr_uri_2"}},
+                "r6gd": {"regional_properties": {"image_uri": "$cpu_ecr_uri_2"}},
+                "r6i": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "r6id": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "r7i": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "t2": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+                "t3": {"regional_properties": {"image_uri": "$scikit_ecr_uri_1"}},
+            },
+        },
+        "dynamic_container_deployment_supported": False,
     },
 }
 
 BASE_SPEC = {
+    "hosting_resource_requirements": {"num_accelerators": 1, "min_memory_mb": 34360},
+    "inference_volume_size": 123,
+    "training_volume_size": 456,
+    "dynamic_container_deployment_supported": True,
     "model_id": "pytorch-ic-mobilenet-v2",
     "url": "https://pytorch.org/hub/pytorch_vision_mobilenet_v2/",
-    "version": "1.0.0",
-    "min_sdk_version": "2.49.0",
-    "training_supported": True,
+    "version": "3.0.6",
+    "min_sdk_version": "2.189.0",
     "incremental_training_supported": True,
-    "gated_bucket": False,
-    "default_payloads": None,
     "hosting_ecr_specs": {
         "framework": "pytorch",
-        "framework_version": "1.5.0",
-        "py_version": "py3",
+        "framework_version": "1.10.0",
+        "py_version": "py38",
     },
-    "hosting_instance_type_variants": None,
+    "hosting_artifact_uri": None,
+    "hosting_artifact_key": "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference/v2.0.0/",
+    "hosting_script_key": "source-directory-tarballs/pytorch/inference/ic/v2.0.0/sourcedir.tar.gz",
+    "training_supported": True,
     "training_ecr_specs": {
         "framework": "pytorch",
-        "framework_version": "1.5.0",
-        "py_version": "py3",
+        "framework_version": "1.10.0",
+        "py_version": "py38",
     },
-    "training_instance_type_variants": None,
-    "hosting_artifact_key": "pytorch-infer/infer-pytorch-ic-mobilenet-v2.tar.gz",
-    "hosting_artifact_uri": None,
-    "training_artifact_key": "pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz",
-    "hosting_script_key": "source-directory-tarballs/pytorch/inference/ic/v1.0.0/sourcedir.tar.gz",
-    "training_script_key": "source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz",
-    "training_prepacked_script_key": None,
-    "hosting_prepacked_artifact_key": None,
-    "training_model_package_artifact_uris": None,
-    "deprecate_warn_message": None,
-    "deprecated_message": None,
-    "hosting_model_package_arns": {},
-    "hosting_eula_key": None,
-    "model_subscription_link": None,
+    "training_artifact_key": "pytorch-training/v2.0.0/train-pytorch-ic-mobilenet-v2.tar.gz",
+    "training_script_key": "source-directory-tarballs/pytorch/transfer_learning/ic/v2.3.0/sourcedir.tar.gz",
     "hyperparameters": [
+        {
+            "name": "train_only_top_layer",
+            "type": "text",
+            "options": ["True", "False"],
+            "default": "True",
+            "scope": "algorithm",
+        },
         {
             "name": "epochs",
             "type": "int",
-            "default": 3,
+            "default": 5,
+            "scope": "algorithm",
             "min": 1,
             "max": 1000,
-            "scope": "algorithm",
         },
         {
-            "name": "adam-learning-rate",
+            "name": "learning_rate",
             "type": "float",
-            "default": 0.05,
+            "default": 0.001,
+            "scope": "algorithm",
             "min": 1e-08,
             "max": 1,
-            "scope": "algorithm",
         },
         {
-            "name": "batch-size",
+            "name": "batch_size",
             "type": "int",
             "default": 4,
+            "scope": "algorithm",
             "min": 1,
             "max": 1024,
+        },
+        {
+            "name": "reinitialize_top_layer",
+            "type": "text",
+            "options": ["Auto", "True", "False"],
+            "default": "Auto",
             "scope": "algorithm",
         },
         {
@@ -8403,60 +15521,398 @@
     "inference_dependencies": [],
     "inference_vulnerabilities": [],
     "training_vulnerable": False,
-    "training_dependencies": [],
+    "training_dependencies": ["sagemaker_jumpstart_prepack_script_utilities==1.0.0"],
     "training_vulnerabilities": [],
     "deprecated": False,
-    "default_inference_instance_type": "ml.p2.xlarge",
+    "usage_info_message": None,
+    "deprecated_message": None,
+    "deprecate_warn_message": None,
+    "default_inference_instance_type": "ml.m5.large",
     "supported_inference_instance_types": [
-        "ml.p2.xlarge",
-        "ml.p3.2xlarge",
-        "ml.g4dn.xlarge",
         "ml.m5.large",
         "ml.m5.xlarge",
         "ml.c5.xlarge",
         "ml.c5.2xlarge",
+        "ml.m4.large",
+        "ml.m4.xlarge",
     ],
-    "default_training_instance_type": "ml.p3.2xlarge",
-    "supported_training_instance_types": [
-        "ml.p3.2xlarge",
-        "ml.p2.xlarge",
-        "ml.g4dn.2xlarge",
-        "ml.m5.xlarge",
-        "ml.c5.2xlarge",
-    ],
-    "hosting_use_script_uri": True,
-    "usage_info_message": None,
-    "metrics": [{"Regex": "val_accuracy: ([0-9\\.]+)", "Name": "pytorch-ic:val-accuracy"}],
-    "model_kwargs": {"some-model-kwarg-key": "some-model-kwarg-value"},
-    "deploy_kwargs": {"some-model-deploy-kwarg-key": "some-model-deploy-kwarg-value"},
-    "estimator_kwargs": {
-        "encrypt_inter_container_traffic": True,
-    },
-    "fit_kwargs": {"some-estimator-fit-key": "some-estimator-fit-value"},
+    "default_training_instance_type": "ml.m5.xlarge",
+    "supported_training_instance_types": ["ml.m5.xlarge", "ml.c5.2xlarge", "ml.m4.xlarge"],
+    "metrics": [{"Name": "pytorch-ic:val-accuracy", "Regex": "val_accuracy: ([0-9\\.]+)"}],
+    "training_prepacked_script_key": "source-directory-tarballs/pytorch/transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz",
+    "hosting_prepacked_artifact_key": "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference-prepack/v1.0.0/",
+    "model_kwargs": {},
+    "deploy_kwargs": {},
+    "estimator_kwargs": {"encrypt_inter_container_traffic": True, "max_run": 360000},
+    "fit_kwargs": {},
     "predictor_specs": {
-        "supported_content_types": ["application/x-image"],
-        "supported_accept_types": ["application/json;verbose", "application/json"],
         "default_content_type": "application/x-image",
+        "supported_content_types": ["application/x-image"],
         "default_accept_type": "application/json",
+        "supported_accept_types": ["application/json;verbose", "application/json"],
     },
-    "inference_volume_size": 123,
-    "training_volume_size": 456,
     "inference_enable_network_isolation": True,
-    "training_enable_network_isolation": False,
-    "resource_name_base": "dfsdfsds",
-    "hosting_resource_requirements": {"num_accelerators": 1, "min_memory_mb": 34360},
-    "dynamic_container_deployment_supported": True,
+    "training_enable_network_isolation": True,
+    "resource_name_base": "pt-ic-mobilenet-v2",
+    "hosting_eula_key": None,
+    "hosting_model_package_arns": {},
+    "training_model_package_artifact_uris": None,
+    "hosting_use_script_uri": False,
+    "hosting_instance_type_variants": {
+        "regional_aliases": {
+            "af-south-1": {
+                "cpu_ecr_uri_1": "626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:1.10.0-gpu-py38",
+            },
+            "ap-east-1": {
+                "cpu_ecr_uri_1": "871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:1.10.0-gpu-py38",
+            },
+            "ap-northeast-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:1.10.0-gpu-py38",
+            },
+            "ap-northeast-2": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
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+            },
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+            },
+            "ap-south-1": {
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+            },
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+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:1.10.0-gpu-py38",
+            },
+            "ap-southeast-3": {
+                "cpu_ecr_uri_1": "907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
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+            "ap-southeast-5": {
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+            "ca-central-1": {
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+            "cn-north-1": {
+                "cpu_ecr_uri_1": "727897471807.dkr.ecr.cn-north-1.amazonaws.com.cn/pytorch-inference:1.10.0-cpu-py38",
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+            },
+            "cn-northwest-1": {
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+            "eu-central-1": {
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+        "variants": {
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+            "c6id": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c7i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "g4dn": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "g5": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "g6": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "g6e": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "local": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "local_gpu": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "m4": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m5": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m5d": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m6i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m6id": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m7i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "p2": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p3": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p3dn": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p4d": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p4de": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p5": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "r5": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r5d": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r6i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r6id": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r7i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "t2": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "t3": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "trn1": {"regional_properties": {"image_uri": "$alias_ecr_uri_3"}},
+            "trn1n": {"regional_properties": {"image_uri": "$alias_ecr_uri_3"}},
+        },
+    },
+    "training_instance_type_variants": {
+        "regional_aliases": {
+            "af-south-1": {
+                "cpu_ecr_uri_1": "626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-east-1": {
+                "cpu_ecr_uri_1": "871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-northeast-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-northeast-2": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-northeast-3": {
+                "cpu_ecr_uri_1": "364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-south-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-southeast-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-southeast-2": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-southeast-3": {
+                "cpu_ecr_uri_1": "907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ap-southeast-5": {
+                "cpu_ecr_uri_1": "550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "ca-central-1": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "cn-north-1": {
+                "cpu_ecr_uri_1": "727897471807.dkr.ecr.cn-north-1.amazonaws.com.cn/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "727897471807.dkr.ecr.cn-north-1.amazonaws.com.cn/pytorch-training:1.10.0-gpu-py38",
+            },
+            "cn-northwest-1": {
+                "cpu_ecr_uri_1": "727897471807.dkr.ecr.cn-northwest-1.amazonaws.com.cn/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "727897471807.dkr.ecr.cn-northwest-1.amazonaws.com.cn/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-central-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-central-2": {
+                "cpu_ecr_uri_1": "380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-north-1": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-south-1": {
+                "cpu_ecr_uri_1": "692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-west-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-west-2": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "eu-west-3": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "il-central-1": {
+                "cpu_ecr_uri_1": "780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "me-central-1": {
+                "cpu_ecr_uri_1": "914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "me-south-1": {
+                "cpu_ecr_uri_1": "217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "sa-east-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "us-east-1": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "us-east-2": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "us-gov-east-1": {
+                "cpu_ecr_uri_1": "446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "us-gov-west-1": {
+                "cpu_ecr_uri_1": "442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "us-west-1": {
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+            "us-west-2": {
+                "alias_ecr_uri_3": "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training-neuron:1.11.0-neuron-py38-sdk2.4.0-ubuntu20.04",
+                "cpu_ecr_uri_1": "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+                "gpu_ecr_uri_2": "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            },
+        },
+        "aliases": None,
+        "variants": {
+            "c4": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c5": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c5d": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c5n": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c6i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c6id": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "c7i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "g4dn": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "g5": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "g6": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "g6e": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "local": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "local_gpu": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "m4": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m5": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m5d": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m6i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m6id": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "m7i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "p2": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p3": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p3dn": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p4d": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p4de": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "p5": {"regional_properties": {"image_uri": "$gpu_ecr_uri_2"}},
+            "r5": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r5d": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r6i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r6id": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "r7i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "t2": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "t3": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}},
+            "trn1": {"regional_properties": {"image_uri": "$alias_ecr_uri_3"}},
+            "trn1n": {"regional_properties": {"image_uri": "$alias_ecr_uri_3"}},
+        },
+    },
+    "default_payloads": None,
+    "gated_bucket": False,
+    "model_subscription_link": None,
+    "hosting_additional_data_sources": None,
+    "hosting_neuron_model_id": None,
+    "hosting_neuron_model_version": None,
     "inference_configs": None,
     "inference_config_components": None,
+    "inference_config_rankings": None,
     "training_configs": None,
     "training_config_components": None,
-    "inference_config_rankings": None,
     "training_config_rankings": None,
-    "hosting_additional_data_sources": None,
-    "hosting_neuron_model_id": None,
-    "hosting_neuron_model_version": None,
 }
-
 BASE_HOSTING_ADDITIONAL_DATA_SOURCES = {
     "hosting_additional_data_sources": {
         "speculative_decoding": [
diff --git a/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py b/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py
index f6666e68ae..1fd2a47aca 100644
--- a/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py
+++ b/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py
@@ -198,6 +198,7 @@ def test_non_prepacked(
             ],
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch("sagemaker.jumpstart.estimator.validate_model_id_and_get_type")
     @mock.patch(
         "sagemaker.jumpstart.factory.model.get_default_jumpstart_session_with_user_agent_suffix"
@@ -220,7 +221,10 @@ def test_prepacked(
         mock_session_estimator: mock.Mock,
         mock_session_model: mock.Mock,
         mock_validate_model_id_and_get_type: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_estimator_deploy.return_value = default_predictor
 
         mock_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
@@ -239,32 +243,71 @@ def test_prepacked(
         mock_estimator_init.assert_called_once_with(
             instance_type="ml.p3.16xlarge",
             instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.10.2"
-            "-transformers4.17.0-gpu-py38-cu113-ubuntu20.04",
-            model_uri="s3://jumpstart-cache-prod-us-west-2/huggingface-training/train-huggingface"
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface"
+            "-pytorch-training:2.0.0-transformers4.28.1-gpu-py310-cu118-ubuntu20.04",
+            model_uri="s3://jumpstart-cache-prod-us-west-2/huggingface-training"
+            "/train-huggingface"
             "-text2text-flan-t5-base.tar.gz",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/huggingface/"
-            "transfer_learning/text2text/prepack/v1.0.1/sourcedir.tar.gz",
+            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs"
+            "/huggingface/transfer_learning/text2text/prepack/v2.0.0/sourcedir.tar.gz",
             entry_point="transfer_learning.py",
             hyperparameters={
                 "epochs": "1",
+                "max_steps": "-1",
                 "seed": "42",
                 "batch_size": "64",
                 "learning_rate": "0.0001",
+                "lr_scheduler_type": "constant_with_warmup",
+                "warmup_ratio": "0.0",
+                "warmup_steps": "0",
                 "validation_split_ratio": "0.05",
                 "train_data_split_seed": "0",
+                "max_train_samples": "-1",
+                "max_eval_samples": "-1",
+                "max_input_length": "-1",
+                "max_output_length": "128",
+                "pad_to_max_length": "True",
+                "gradient_accumulation_steps": "1",
+                "weight_decay": "0.0",
+                "adam_beta1": "0.9",
+                "adam_beta2": "0.999",
+                "adam_epsilon": "1e-08",
+                "max_grad_norm": "1.0",
+                "load_best_model_at_end": "True",
+                "early_stopping_patience": "3",
+                "early_stopping_threshold": "0.0",
+                "label_smoothing_factor": "0",
+                "logging_strategy": "steps",
+                "logging_first_step": "False",
+                "logging_steps": "500",
+                "logging_nan_inf_filter": "True",
+                "save_strategy": "epoch",
+                "save_steps": "500",
+                "save_total_limit": "2",
+                "dataloader_drop_last": "False",
+                "dataloader_num_workers": "0",
+                "evaluation_strategy": "epoch",
+                "eval_steps": "500",
+                "eval_accumulation_steps": "None",
+                "gradient_checkpointing": "True",
+                "auto_find_batch_size": "False",
+                "preprocessing_num_workers": "None",
+                "peft_type": "none",
             },
             metric_definitions=[
                 {"Name": "huggingface-text2text:eval-loss", "Regex": "'eval_loss': ([0-9\\.]+)"}
             ],
             role=execution_role,
-            encrypt_inter_container_traffic=False,
+            encrypt_inter_container_traffic=True,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
             tags=[
                 {"Key": JumpStartTag.MODEL_ID, "Value": "js-trainable-model-prepacked"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.2.0"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "2.2.3"},
             ],
+            volume_size=512,
+            max_run=360000,
+            disable_output_compression=True,
         )
 
         channels = {
@@ -274,31 +317,41 @@ def test_prepacked(
 
         estimator.fit(channels)
 
-        mock_estimator_fit.assert_called_once_with(inputs=channels, wait=True)
+        mock_estimator_fit.assert_called_once_with(
+            inputs=channels, wait=True, job_name="hf-text2text-flan-t5-base-8675309"
+        )
 
         estimator.deploy()
 
         mock_estimator_deploy.assert_called_once_with(
-            instance_type="ml.g5.xlarge",
+            instance_type="ml.g5.2xlarge",
             initial_instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:"
-            "1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/"
+            "huggingface-pytorch-tgi-inference:2.1.1-tgi1.4.0-gpu-py310-cu121-ubuntu20.04",
             env={
                 "SAGEMAKER_PROGRAM": "inference.py",
                 "ENDPOINT_SERVER_TIMEOUT": "3600",
                 "MODEL_CACHE_ROOT": "/opt/ml/model",
                 "SAGEMAKER_ENV": "1",
+                "HF_MODEL_ID": "/opt/ml/model",
+                "SM_NUM_GPUS": "1",
+                "MAX_INPUT_LENGTH": "1024",
+                "MAX_TOTAL_TOKENS": "2048",
                 "SAGEMAKER_MODEL_SERVER_WORKERS": "1",
             },
             predictor_cls=Predictor,
+            endpoint_name="hf-text2text-flan-t5-base-8675309",
             role=execution_role,
             wait=True,
             use_compiled_model=False,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
             tags=[
                 {"Key": JumpStartTag.MODEL_ID, "Value": "js-trainable-model-prepacked"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.2.0"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "2.2.3"},
             ],
+            model_data_download_timeout=1200,
+            container_startup_health_check_timeout=1200,
+            model_name="hf-text2text-flan-t5-base-8675309",
         )
 
     @mock.patch("sagemaker.utils.sagemaker_timestamp")
@@ -361,12 +414,48 @@ def test_gated_model_s3_uri(
         estimator = JumpStartEstimator(model_id=model_id, environment={"accept_eula": "true"})
 
         mock_estimator_init.assert_called_once_with(
-            instance_type="ml.p3.2xlarge",
+            instance_type="ml.g5.12xlarge",
             instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-"
+            "pytorch-training:2.0.0-transformers4.28.1-gpu-py310-cu118-ubuntu20.04",
             source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
-            "meta/transfer_learning/textgeneration/v1.0.0/sourcedir.tar.gz",
+            "meta/transfer_learning/textgeneration/v1.0.6/sourcedir.tar.gz",
             entry_point="transfer_learning.py",
+            hyperparameters={
+                "int8_quantization": "False",
+                "enable_fsdp": "True",
+                "epoch": "1",
+                "learning_rate": "0.0001",
+                "lora_r": "8",
+                "lora_alpha": "32",
+                "lora_dropout": "0.05",
+                "instruction_tuned": "False",
+                "chat_dataset": "True",
+                "add_input_output_demarcation_key": "True",
+                "per_device_train_batch_size": "1",
+                "per_device_eval_batch_size": "1",
+                "max_train_samples": "-1",
+                "max_val_samples": "-1",
+                "seed": "10",
+                "max_input_length": "-1",
+                "validation_split_ratio": "0.2",
+                "train_data_split_seed": "0",
+                "preprocessing_num_workers": "None",
+            },
+            metric_definitions=[
+                {
+                    "Name": "huggingface-textgeneration:eval-loss",
+                    "Regex": "eval_epoch_loss=tensor\\(([0-9\\.]+)",
+                },
+                {
+                    "Name": "huggingface-textgeneration:eval-ppl",
+                    "Regex": "eval_ppl=tensor\\(([0-9\\.]+)",
+                },
+                {
+                    "Name": "huggingface-textgeneration:train-loss",
+                    "Regex": "train_epoch_loss=([0-9\\.]+)",
+                },
+            ],
             role=execution_role,
             sagemaker_session=sagemaker_session,
             max_run=360000,
@@ -374,14 +463,15 @@ def test_gated_model_s3_uri(
             encrypt_inter_container_traffic=True,
             environment={
                 "accept_eula": "true",
-                "SageMakerGatedModelS3Uri": "s3://jumpstart-cache-alpha-us-west-2/dummy.tar.gz",
+                "SageMakerGatedModelS3Uri": "s3://sagemaker-repository-pdx/"
+                "model-data-model-package_llama2-7b-f-v4-71eeccf76ddf33f2a18d2e16b9c7f302",
             },
             tags=[
                 {
                     "Key": "sagemaker-sdk:jumpstart-model-id",
                     "Value": "js-gated-artifact-trainable-model",
                 },
-                {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.0.0"},
+                {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.0.4"},
             ],
         )
 
@@ -403,7 +493,7 @@ def test_gated_model_s3_uri(
             initial_instance_count=1,
             predictor_cls=Predictor,
             endpoint_name="meta-textgeneration-llama-2-7b-f-8675309",
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118",
             wait=True,
             model_data_download_timeout=3600,
             container_startup_health_check_timeout=3600,
@@ -416,7 +506,7 @@ def test_gated_model_s3_uri(
                     "Key": "sagemaker-sdk:jumpstart-model-id",
                     "Value": "js-gated-artifact-trainable-model",
                 },
-                {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.0.0"},
+                {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.0.4"},
             ],
         )
 
@@ -619,7 +709,7 @@ def test_jumpstart_model_package_artifact_s3_uri_unsupported_region(
         assert (
             str(e.value) == "Model package artifact s3 uri for 'js-gated-artifact-trainable-model' "
             "not supported in eu-north-1. Please try one of the following regions: "
-            "us-west-2, us-east-1, eu-west-1, ap-southeast-1."
+            "us-west-2, us-east-2, us-east-1, eu-west-1, ap-southeast-1, ap-southeast-2."
         )
 
     @mock.patch("sagemaker.jumpstart.estimator.validate_model_id_and_get_type")
@@ -996,7 +1086,7 @@ def test_jumpstart_estimator_tags(
 
         js_tags = [
             {"Key": "sagemaker-sdk:jumpstart-model-id", "Value": "js-trainable-model-prepacked"},
-            {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "1.2.0"},
+            {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.2.3"},
         ]
 
         self.assertEqual(
@@ -1829,59 +1919,68 @@ def test_model_artifact_variant_estimator(
         mock_session.return_value = sagemaker_session
 
         # this instance type has a special model artifact
-        JumpStartEstimator(model_id=model_id, instance_type="ml.p2.xlarge")
+        JumpStartEstimator(model_id=model_id, instance_type="ml.m5.xlarge")
 
         mock_estimator_init.assert_called_once_with(
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
             instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:1.13.1"
-            "-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
-            model_uri="s3://jumpstart-cache-prod-us-west-2/hello-mars-1",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.10.0-cpu-py38",
+            model_uri="s3://jumpstart-cache-prod-us-west-2/hello-world-1",
             source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
-            "pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz",
+            "pytorch/transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz",
             entry_point="transfer_learning.py",
-            hyperparameters={"epochs": "3", "adam-learning-rate": "0.05", "batch-size": "4"},
+            hyperparameters={
+                "train_only_top_layer": "True",
+                "epochs": "5",
+                "learning_rate": "0.001",
+                "batch_size": "4",
+                "reinitialize_top_layer": "Auto",
+            },
             metric_definitions=[
-                {"Regex": "val_accuracy: ([0-9\\.]+)", "Name": "pytorch-ic:val-accuracy"}
+                {"Name": "pytorch-ic:val-accuracy", "Regex": "val_accuracy: ([0-9\\.]+)"}
             ],
             role=execution_role,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
             encrypt_inter_container_traffic=True,
-            volume_size=456,
+            max_run=360000,
             tags=[
                 {"Key": JumpStartTag.MODEL_ID, "Value": "model-artifact-variant-model"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
             ],
         )
 
         mock_estimator_init.reset_mock()
 
-        JumpStartEstimator(model_id=model_id, instance_type="ml.p99.xlarge")
+        JumpStartEstimator(model_id=model_id, instance_type="ml.p3.2xlarge")
 
         mock_estimator_init.assert_called_once_with(
-            instance_type="ml.p99.xlarge",
+            instance_type="ml.p3.2xlarge",
             instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.5.0-gpu-py3",
-            model_uri="s3://jumpstart-cache-prod-us-west-2/pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/pytorch/"
-            "transfer_learning/ic/v1.0.0/sourcedir.tar.gz",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:1.10.0-gpu-py38",
+            model_uri="s3://jumpstart-cache-prod-us-west-2/pytorch-training/"
+            "v2.0.0/train-pytorch-ic-mobilenet-v2.tar.gz",
+            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
+            "pytorch/transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz",
             entry_point="transfer_learning.py",
-            hyperparameters={"epochs": "3", "adam-learning-rate": "0.05", "batch-size": "4"},
+            hyperparameters={
+                "train_only_top_layer": "True",
+                "epochs": "5",
+                "learning_rate": "0.001",
+                "batch_size": "4",
+                "reinitialize_top_layer": "Auto",
+            },
             metric_definitions=[
-                {"Regex": "val_accuracy: ([0-9\\.]+)", "Name": "pytorch-ic:val-accuracy"}
+                {"Name": "pytorch-ic:val-accuracy", "Regex": "val_accuracy: ([0-9\\.]+)"}
             ],
             role=execution_role,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
             encrypt_inter_container_traffic=True,
-            volume_size=456,
+            max_run=360000,
             tags=[
-                {
-                    "Key": "sagemaker-sdk:jumpstart-model-id",
-                    "Value": "model-artifact-variant-model",
-                },
-                {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "model-artifact-variant-model"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
             ],
         )
 
@@ -1935,6 +2034,7 @@ def test_jumpstart_estimator_session(
         assert len(s3_clients) == 1
         assert list(s3_clients)[0] == session.s3_client
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor._get_manifest")
     @mock.patch("sagemaker.jumpstart.factory.estimator.Session")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
@@ -1948,14 +2048,18 @@ def test_estimator_initialization_with_config_name(
         mock_get_model_specs: mock.Mock,
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_get_model_specs.side_effect = get_prototype_spec_with_configs
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_estimator_fit.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -1964,31 +2068,43 @@ def test_estimator_initialization_with_config_name(
             config_name="gpu-training",
         )
 
-        mock_estimator_init.assert_called_once_with(
+        mock_estimator_init.assert_called_with(
             instance_type="ml.p2.xlarge",
             instance_count=1,
             image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/"
             "huggingface-pytorch-training:1.13.1-neuronx-py310-sdk2.14.1-ubuntu20.04",
-            model_uri="s3://jumpstart-cache-prod-us-west-2/artifacts/meta-textgeneration-llama-2-7b/"
-            "gpu-training/model/",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/pytorch/transfer_learning/"
-            "eqa/v1.0.0/sourcedir.tar.gz",
+            model_uri="s3://jumpstart-cache-prod-us-west-2/artifacts/"
+            "meta-textgeneration-llama-2-7b/gpu-training/model/",
+            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
+            "pytorch/transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz",
             entry_point="transfer_learning.py",
-            hyperparameters={"epochs": "3", "adam-learning-rate": "2e-05", "batch-size": "4"},
+            hyperparameters={
+                "train_only_top_layer": "True",
+                "epochs": "5",
+                "learning_rate": "0.001",
+                "batch_size": "4",
+                "reinitialize_top_layer": "Auto",
+            },
+            metric_definitions=[
+                {"Name": "pytorch-ic:val-accuracy", "Regex": "val_accuracy: ([0-9\\.]+)"}
+            ],
             role="fake role! do not use!",
+            max_run=360000,
             sagemaker_session=estimator.sagemaker_session,
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.TRAINING_CONFIG_NAME, "Value": "gpu-training"},
             ],
-            enable_network_isolation=False,
+            enable_network_isolation=True,
+            encrypt_inter_container_traffic=True,
         )
 
         estimator.fit()
 
-        mock_estimator_fit.assert_called_once_with(wait=True)
+        mock_estimator_fit.assert_called_once_with(wait=True, job_name="pt-ic-mobilenet-v2-8675309")
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor._get_manifest")
     @mock.patch("sagemaker.jumpstart.factory.estimator.Session")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
@@ -2002,14 +2118,18 @@ def test_estimator_set_config_name(
         mock_get_model_specs: mock.Mock,
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_get_model_specs.side_effect = get_prototype_spec_with_configs
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_estimator_fit.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -2024,24 +2144,36 @@ def test_estimator_set_config_name(
             "pytorch-training:1.13.1-py310-sdk2.14.1-ubuntu20.04",
             model_uri="s3://jumpstart-cache-prod-us-west-2/artifacts/meta-textgeneration-llama-2-7b/"
             "gpu-training-budget/model/",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/pytorch/"
-            "transfer_learning/eqa/v1.0.0/sourcedir.tar.gz",
+            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
+            "pytorch/transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz",
             entry_point="transfer_learning.py",
-            hyperparameters={"epochs": "3", "adam-learning-rate": "2e-05", "batch-size": "4"},
+            hyperparameters={
+                "train_only_top_layer": "True",
+                "epochs": "5",
+                "learning_rate": "0.001",
+                "batch_size": "4",
+                "reinitialize_top_layer": "Auto",
+            },
+            metric_definitions=[
+                {"Name": "pytorch-ic:val-accuracy", "Regex": "val_accuracy: ([0-9\\.]+)"}
+            ],
             role="fake role! do not use!",
+            max_run=360000,
             sagemaker_session=estimator.sagemaker_session,
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.TRAINING_CONFIG_NAME, "Value": "gpu-training-budget"},
             ],
-            enable_network_isolation=False,
+            enable_network_isolation=True,
+            encrypt_inter_container_traffic=True,
         )
 
         estimator.fit()
 
-        mock_estimator_fit.assert_called_once_with(wait=True)
+        mock_estimator_fit.assert_called_once_with(wait=True, job_name="pt-ic-mobilenet-v2-8675309")
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor._get_manifest")
     @mock.patch("sagemaker.jumpstart.factory.estimator.Session")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
@@ -2055,7 +2187,9 @@ def test_estimator_default_inference_config(
         mock_get_model_specs: mock.Mock,
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+        mock_sagemaker_timestamp.return_value = "8675309"
         mock_estimator_deploy.return_value = default_predictor
         mock_get_model_specs.side_effect = get_prototype_spec_with_configs
         mock_get_manifest.side_effect = (
@@ -2063,7 +2197,7 @@ def test_estimator_default_inference_config(
         )
         mock_estimator_fit.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -2074,23 +2208,28 @@ def test_estimator_default_inference_config(
         estimator.deploy()
 
         mock_estimator_deploy.assert_called_once_with(
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.large",
             initial_instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-hosting"
-            ":2.0.0-transformers4.28.1-gpu-py310-cu118-ubuntu20.04",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
-            "pytorch/inference/eqa/v1.0.0/sourcedir.tar.gz",
-            entry_point="inference.py",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
+            env={
+                "SAGEMAKER_PROGRAM": "inference.py",
+                "ENDPOINT_SERVER_TIMEOUT": "3600",
+                "MODEL_CACHE_ROOT": "/opt/ml/model",
+                "SAGEMAKER_ENV": "1",
+                "SAGEMAKER_MODEL_SERVER_WORKERS": "1",
+            },
             predictor_cls=Predictor,
             wait=True,
             role="fake role! do not use!",
             use_compiled_model=False,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "gpu-inference"},
             ],
+            model_name="pt-ic-mobilenet-v2-8675309",
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
     @mock.patch("sagemaker.jumpstart.estimator.JumpStartEstimator._attach")
@@ -2112,7 +2251,7 @@ def test_estimator_incremental_training_config(
         mock_attach: mock.Mock,
     ):
         mock_get_model_info_from_training_job.return_value = (
-            "pytorch-eqa-bert-base-cased",
+            "pytorch-ic-mobilenet-v2",
             "1.0.0",
             None,
             "gpu-training-budget",
@@ -2123,7 +2262,7 @@ def test_estimator_incremental_training_config(
         )
         mock_estimator_fit.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -2140,7 +2279,7 @@ def test_estimator_incremental_training_config(
             sagemaker_session=mock_session,
             model_channel_name="model",
             additional_kwargs={
-                "model_id": "pytorch-eqa-bert-base-cased",
+                "model_id": "pytorch-ic-mobilenet-v2",
                 "model_version": "1.0.0",
                 "tolerate_vulnerable_model": True,
                 "tolerate_deprecated_model": True,
@@ -2148,6 +2287,7 @@ def test_estimator_incremental_training_config(
             },
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor._get_manifest")
     @mock.patch("sagemaker.jumpstart.factory.estimator.Session")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
@@ -2163,7 +2303,10 @@ def test_estimator_deploy_with_config(
         mock_get_model_specs: mock.Mock,
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
         mock_estimator_deploy.return_value = default_predictor
         mock_get_model_specs.side_effect = get_prototype_spec_with_configs
         mock_get_manifest.side_effect = (
@@ -2171,7 +2314,7 @@ def test_estimator_deploy_with_config(
         )
         mock_estimator_fit.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -2182,23 +2325,28 @@ def test_estimator_deploy_with_config(
         estimator.deploy()
 
         mock_estimator_deploy.assert_called_once_with(
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.large",
             initial_instance_count=1,
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/"
-            "pytorch-hosting:1.13.1-py310-sdk2.14.1-ubuntu20.04",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
-            "pytorch/inference/eqa/v1.0.0/sourcedir.tar.gz",
-            entry_point="inference.py",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
+            env={
+                "SAGEMAKER_PROGRAM": "inference.py",
+                "ENDPOINT_SERVER_TIMEOUT": "3600",
+                "MODEL_CACHE_ROOT": "/opt/ml/model",
+                "SAGEMAKER_ENV": "1",
+                "SAGEMAKER_MODEL_SERVER_WORKERS": "1",
+            },
             predictor_cls=Predictor,
             wait=True,
             role="fake role! do not use!",
             use_compiled_model=False,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "gpu-inference-budget"},
             ],
+            model_name="pt-ic-mobilenet-v2-8675309",
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
 
diff --git a/tests/unit/sagemaker/jumpstart/model/test_model.py b/tests/unit/sagemaker/jumpstart/model/test_model.py
index 09e63f8f59..be961828f4 100644
--- a/tests/unit/sagemaker/jumpstart/model/test_model.py
+++ b/tests/unit/sagemaker/jumpstart/model/test_model.py
@@ -280,8 +280,15 @@ def test_non_prepacked_inference_component_based_endpoint_no_default_pass_custom
         mock_model_init.assert_called_once_with(
             image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:"
             "1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04",
-            model_data="s3://jumpstart-cache-prod-us-west-2/huggingface-infer/prepack/"
-            "v1.0.0/infer-prepack-huggingface-txt2img-conflictx-complex-lineart.tar.gz",
+            model_data={
+                "S3DataSource": {
+                    "S3Uri": "s3://jumpstart-cache-prod-us-west-2/"
+                    "huggingface-txt2img/huggingface-txt2img-conflictx"
+                    "-complex-lineart/artifacts/inference-prepack/v1.0.0/",
+                    "S3DataType": "S3Prefix",
+                    "CompressionType": "None",
+                }
+            },
             env={
                 "SAGEMAKER_PROGRAM": "inference.py",
                 "ENDPOINT_SERVER_TIMEOUT": "3600",
@@ -292,7 +299,8 @@ def test_non_prepacked_inference_component_based_endpoint_no_default_pass_custom
             predictor_cls=Predictor,
             role=execution_role,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
+            name="hf-txt2img-conflictx-complex-lineart-7777",
         )
 
         custom_resource_requirements = ResourceRequirements(
@@ -314,13 +322,15 @@ def test_non_prepacked_inference_component_based_endpoint_no_default_pass_custom
             wait=True,
             tags=[
                 {"Key": JumpStartTag.MODEL_ID, "Value": "js-model-class-model-prepacked"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.1.0"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "2.0.3"},
             ],
             endpoint_logging=False,
             resources=custom_resource_requirements,
             endpoint_type=EndpointType.INFERENCE_COMPONENT_BASED,
+            endpoint_name="hf-txt2img-conflictx-complex-lineart-7777",
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -340,7 +350,9 @@ def test_prepacked(
         mock_session: mock.Mock,
         mock_validate_model_id_and_get_type: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+        mock_sagemaker_timestamp.return_value = "8675309"
         mock_model_deploy.return_value = default_predictor
 
         mock_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
@@ -358,8 +370,15 @@ def test_prepacked(
         mock_model_init.assert_called_once_with(
             image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:"
             "1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04",
-            model_data="s3://jumpstart-cache-prod-us-west-2/huggingface-infer/prepack/"
-            "v1.0.0/infer-prepack-huggingface-txt2img-conflictx-complex-lineart.tar.gz",
+            model_data={
+                "S3DataSource": {
+                    "S3Uri": "s3://jumpstart-cache-prod-us-west-2/"
+                    "huggingface-txt2img/huggingface-txt2img-conflictx"
+                    "-complex-lineart/artifacts/inference-prepack/v1.0.0/",
+                    "S3DataType": "S3Prefix",
+                    "CompressionType": "None",
+                }
+            },
             env={
                 "SAGEMAKER_PROGRAM": "inference.py",
                 "ENDPOINT_SERVER_TIMEOUT": "3600",
@@ -370,7 +389,8 @@ def test_prepacked(
             predictor_cls=Predictor,
             role=execution_role,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
+            name="hf-txt2img-conflictx-complex-lineart-8675309",
         )
 
         model.deploy()
@@ -378,10 +398,11 @@ def test_prepacked(
         mock_model_deploy.assert_called_once_with(
             initial_instance_count=1,
             instance_type="ml.p3.2xlarge",
+            endpoint_name="hf-txt2img-conflictx-complex-lineart-8675309",
             wait=True,
             tags=[
                 {"Key": JumpStartTag.MODEL_ID, "Value": "js-model-class-model-prepacked"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.1.0"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "2.0.3"},
             ],
             endpoint_logging=False,
         )
@@ -1089,7 +1110,7 @@ def test_jumpstart_model_tags(
 
         js_tags = [
             {"Key": "sagemaker-sdk:jumpstart-model-id", "Value": "env-var-variant-model"},
-            {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "1.0.0"},
+            {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "1.6.2"},
         ]
 
         self.assertEqual(
@@ -1171,8 +1192,8 @@ def test_jumpstart_model_package_arn(
         self.assertEqual(
             mock_session.create_model.call_args[0][2],
             {
-                "ModelPackageName": "arn:aws:sagemaker:us-west-2:594846645681:model-package"
-                "/llama2-7b-f-e46eb8a833643ed58aaccd81498972c3"
+                "ModelPackageName": "arn:aws:sagemaker:us-west-2:594846645681:"
+                "model-package/llama2-7b-f-v4-71eeccf76ddf33f2a18d2e16b9c7f302"
             },
         )
 
@@ -1250,10 +1271,11 @@ def test_jumpstart_model_package_arn_unsupported_region(
         mock_session.return_value = MagicMock(sagemaker_config={})
 
         with pytest.raises(ValueError) as e:
-            JumpStartModel(model_id=model_id, region="us-east-2")
+            JumpStartModel(model_id=model_id, region="us-west-1")
         assert (
             str(e.value) == "Model package arn for 'js-model-package-arn' not supported in "
-            "us-east-2. Please try one of the following regions: us-west-2, us-east-1."
+            "us-west-1. Please try one of the following regions: "
+            "us-west-2, us-east-2, us-east-1, eu-west-1, ap-southeast-1, ap-southeast-2."
         )
 
     @mock.patch(
@@ -1328,6 +1350,7 @@ def test_model_data_s3_prefix_override(
             '"S3DataType": "S3Prefix", "CompressionType": "None"}}',
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -1349,7 +1372,11 @@ def test_model_data_s3_prefix_model(
         mock_session: mock.Mock,
         mock_validate_model_id_and_get_type: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_model_deploy.return_value = default_predictor
 
         mock_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
@@ -1362,22 +1389,28 @@ def test_model_data_s3_prefix_model(
         JumpStartModel(model_id=model_id, instance_type="ml.p2.xlarge")
 
         mock_model_init.assert_called_once_with(
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.12.0-gpu-py38",
-            model_data={
-                "S3DataSource": {
-                    "S3Uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-infer/prepack/v1.0.1/",
-                    "S3DataType": "S3Prefix",
-                    "CompressionType": "None",
-                }
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-"
+            "pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
+            model_data="s3://jumpstart-cache-prod-us-west-2/huggingface-infer/"
+            "prepack/v1.1.2/infer-prepack-huggingface-text2text-flan-t5-xxl-fp16.tar.gz",
+            env={
+                "SAGEMAKER_PROGRAM": "inference.py",
+                "ENDPOINT_SERVER_TIMEOUT": "3600",
+                "MODEL_CACHE_ROOT": "/opt/ml/model",
+                "SAGEMAKER_ENV": "1",
+                "TS_DEFAULT_WORKERS_PER_MODEL": "1",
+                "SAGEMAKER_MODEL_SERVER_WORKERS": "1",
             },
             predictor_cls=Predictor,
             role=execution_role,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
+            name="hf-text2text-flan-t5-xxl-fp16-8675309",
         )
 
         mock_js_info_logger.assert_not_called()
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -1399,7 +1432,11 @@ def test_model_artifact_variant_model(
         mock_session: mock.Mock,
         mock_validate_model_id_and_get_type: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_model_deploy.return_value = default_predictor
 
         mock_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS
@@ -1413,8 +1450,7 @@ def test_model_artifact_variant_model(
         JumpStartModel(model_id=model_id, instance_type="ml.p2.xlarge")
 
         mock_model_init.assert_called_once_with(
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-"
-            "inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.10.0-gpu-py38",
             model_data="s3://jumpstart-cache-prod-us-west-2/hello-world-1",
             env={
                 "SAGEMAKER_PROGRAM": "inference.py",
@@ -1427,15 +1463,24 @@ def test_model_artifact_variant_model(
             role=execution_role,
             sagemaker_session=sagemaker_session,
             enable_network_isolation=True,
+            name="pt-ic-mobilenet-v2-8675309",
         )
 
         mock_model_init.reset_mock()
 
-        JumpStartModel(model_id=model_id, instance_type="ml.p99.xlarge")
+        JumpStartModel(model_id=model_id, instance_type="ml.p3.2xlarge")
 
         mock_model_init.assert_called_once_with(
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.5.0-gpu-py3",
-            model_data="s3://jumpstart-cache-prod-us-west-2/basfsdfssf",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/"
+            "pytorch-inference:1.10.0-gpu-py38",
+            model_data={
+                "S3DataSource": {
+                    "S3Uri": "s3://jumpstart-cache-prod-us-west-2/"
+                    "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference-prepack/v1.0.0/",
+                    "S3DataType": "S3Prefix",
+                    "CompressionType": "None",
+                }
+            },
             env={
                 "SAGEMAKER_PROGRAM": "inference.py",
                 "ENDPOINT_SERVER_TIMEOUT": "3600",
@@ -1447,6 +1492,7 @@ def test_model_artifact_variant_model(
             role=execution_role,
             sagemaker_session=sagemaker_session,
             enable_network_isolation=True,
+            name="pt-ic-mobilenet-v2-8675309",
         )
 
     @mock.patch("sagemaker.jumpstart.model.get_model_info_from_endpoint")
@@ -1540,7 +1586,7 @@ def test_model_registry_accept_and_response_types(
 
         mock_model_register.assert_called_once_with(
             model_type=JumpStartModelType.OPEN_WEIGHTS,
-            content_types=["application/x-text"],
+            content_types=["application/x-text", "application/json"],
             response_types=["application/json;verbose", "application/json"],
             model_package_group_name=model.model_id,
         )
@@ -1595,6 +1641,7 @@ def test_jumpstart_model_session(
         assert len(s3_clients) == 1
         assert list(s3_clients)[0] == session.s3_client
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -1619,32 +1666,38 @@ def test_model_local_mode(
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_get_model_specs.side_effect = get_prototype_model_spec
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
-        model = JumpStartModel(model_id=model_id, instance_type="ml.p2.xlarge")
+        model = JumpStartModel(model_id=model_id, instance_type="ml.m5.xlarge")
 
         model.deploy()
 
         mock_model_deploy.assert_called_once_with(
             initial_instance_count=1,
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.xlarge",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -1660,14 +1713,17 @@ def test_model_initialization_with_config_name(
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
         mock_get_model_specs.side_effect = get_prototype_spec_with_configs
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -1681,14 +1737,16 @@ def test_model_initialization_with_config_name(
             initial_instance_count=1,
             instance_type="ml.inf2.xlarge",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "neuron-inference"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -1704,14 +1762,17 @@ def test_model_set_deployment_config(
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
         mock_get_model_specs.side_effect = get_prototype_model_spec
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -1723,13 +1784,14 @@ def test_model_set_deployment_config(
 
         mock_model_deploy.assert_called_once_with(
             initial_instance_count=1,
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.large",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
         mock_get_model_specs.reset_mock()
@@ -1745,12 +1807,13 @@ def test_model_set_deployment_config(
             initial_instance_count=1,
             instance_type="ml.inf2.2xlarge",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "neuron-inference"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
         mock_model_deploy.reset_mock()
         model.set_deployment_config("neuron-inference", "ml.inf2.xlarge")
@@ -1763,14 +1826,16 @@ def test_model_set_deployment_config(
             initial_instance_count=1,
             instance_type="ml.inf2.xlarge",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "neuron-inference"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -1786,15 +1851,18 @@ def test_model_set_deployment_config_and_deploy_for_gated_draft_model(
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
         # WHERE
+
+        mock_sagemaker_timestamp.return_value = "8675309"
         mock_get_model_specs.side_effect = append_gated_draft_model_specs_to_jumpstart_model_spec
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id = "pytorch-eqa-bert-base-cased"
+        model_id = "pytorch-ic-mobilenet-v2"
 
         mock_session.return_value = sagemaker_session
 
@@ -1804,21 +1872,20 @@ def test_model_set_deployment_config_and_deploy_for_gated_draft_model(
 
         # WHEN
         model.deploy(
-            model_access_configs={
-                "pytorch-eqa-bert-base-cased": ModelAccessConfig(accept_eula=True)
-            }
+            model_access_configs={"pytorch-ic-mobilenet-v2": ModelAccessConfig(accept_eula=True)}
         )
 
         # THEN
         mock_model_deploy.assert_called_once_with(
             initial_instance_count=1,
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.large",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
     @mock.patch(
@@ -1844,7 +1911,7 @@ def test_model_set_deployment_config_and_deploy_for_gated_draft_model_no_model_a
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id = "pytorch-eqa-bert-base-cased"
+        model_id = "pytorch-ic-mobilenet-v2"
 
         mock_session.return_value = sagemaker_session
 
@@ -1856,6 +1923,7 @@ def test_model_set_deployment_config_and_deploy_for_gated_draft_model_no_model_a
         with self.assertRaises(ValueError):
             model.deploy()
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor._get_manifest")
     @mock.patch(
         "sagemaker.jumpstart.factory.model.get_default_jumpstart_session_with_user_agent_suffix"
@@ -1871,7 +1939,11 @@ def test_model_deployment_config_additional_model_data_source(
         mock_get_model_specs: mock.Mock,
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_session.return_value = sagemaker_session
         mock_get_model_specs.side_effect = get_prototype_spec_with_configs
         mock_get_manifest.side_effect = (
@@ -1879,22 +1951,32 @@ def test_model_deployment_config_additional_model_data_source(
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         model = JumpStartModel(model_id=model_id, config_name="gpu-accelerated")
 
         mock_model_init.assert_called_once_with(
-            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/"
-            "pytorch-hosting-neuronx:1.13.1-neuronx-py310-sdk2.14.1-ubuntu20.04",
-            model_data="s3://jumpstart-cache-prod-us-west-2/pytorch-infer/"
-            "infer-pytorch-eqa-bert-base-cased.tar.gz",
-            source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
-            "pytorch/inference/eqa/v1.0.0/sourcedir.tar.gz",
-            entry_point="inference.py",
+            image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:1.10.0-cpu-py38",
+            model_data={
+                "S3DataSource": {
+                    "S3Uri": "s3://jumpstart-cache-prod-us-west-2/pytorch-ic"
+                    "/pytorch-ic-mobilenet-v2/artifacts/inference-prepack/v1.0.0/",
+                    "S3DataType": "S3Prefix",
+                    "CompressionType": "None",
+                }
+            },
+            env={
+                "SAGEMAKER_PROGRAM": "inference.py",
+                "ENDPOINT_SERVER_TIMEOUT": "3600",
+                "MODEL_CACHE_ROOT": "/opt/ml/model",
+                "SAGEMAKER_ENV": "1",
+                "SAGEMAKER_MODEL_SERVER_WORKERS": "1",
+            },
             predictor_cls=Predictor,
             role=execution_role,
             sagemaker_session=sagemaker_session,
-            enable_network_isolation=False,
+            enable_network_isolation=True,
+            name="pt-ic-mobilenet-v2-8675309",
             additional_model_data_sources=[
                 {
                     "ChannelName": "draft_model_name",
@@ -1913,14 +1995,15 @@ def test_model_deployment_config_additional_model_data_source(
 
         mock_model_deploy.assert_called_once_with(
             initial_instance_count=1,
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.large",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
                 {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "gpu-accelerated"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
     # TODO: Commenting out this test due to flakiness. Need to mock the session
@@ -1992,6 +2075,7 @@ def test_model_deployment_config_additional_model_data_source(
     #         endpoint_logging=False,
     #     )
 
+    @mock.patch("sagemaker.utils.sagemaker_timestamp")
     @mock.patch(
         "sagemaker.jumpstart.model.get_jumpstart_configs", side_effect=lambda *args, **kwargs: {}
     )
@@ -2007,14 +2091,17 @@ def test_model_set_deployment_config_incompatible_instance_type_or_name(
         mock_session: mock.Mock,
         mock_get_manifest: mock.Mock,
         mock_get_jumpstart_configs: mock.Mock,
+        mock_sagemaker_timestamp: mock.Mock,
     ):
+        mock_sagemaker_timestamp.return_value = "8675309"
+
         mock_get_model_specs.side_effect = get_prototype_model_spec
         mock_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
         )
         mock_model_deploy.return_value = default_predictor
 
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_session.return_value = sagemaker_session
 
@@ -2026,13 +2113,14 @@ def test_model_set_deployment_config_incompatible_instance_type_or_name(
 
         mock_model_deploy.assert_called_once_with(
             initial_instance_count=1,
-            instance_type="ml.p2.xlarge",
+            instance_type="ml.m5.large",
             tags=[
-                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-eqa-bert-base-cased"},
-                {"Key": JumpStartTag.MODEL_VERSION, "Value": "1.0.0"},
+                {"Key": JumpStartTag.MODEL_ID, "Value": "pytorch-ic-mobilenet-v2"},
+                {"Key": JumpStartTag.MODEL_VERSION, "Value": "3.0.6"},
             ],
             wait=True,
             endpoint_logging=False,
+            endpoint_name="pt-ic-mobilenet-v2-8675309",
         )
 
         mock_get_model_specs.reset_mock()
@@ -2059,7 +2147,7 @@ def test_model_list_deployment_configs(
         mock_verify_model_region_and_return_specs: mock.Mock,
         mock_get_init_kwargs: mock.Mock,
     ):
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_get_init_kwargs.side_effect = lambda *args, **kwargs: get_mock_init_kwargs(model_id)
         mock_verify_model_region_and_return_specs.side_effect = (
@@ -2094,7 +2182,7 @@ def test_model_list_deployment_configs_empty(
         mock_get_manifest: mock.Mock,
         mock_verify_model_region_and_return_specs: mock.Mock,
     ):
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_verify_model_region_and_return_specs.side_effect = (
             lambda *args, **kwargs: get_special_model_spec(model_id="gemma-model")
@@ -2130,7 +2218,7 @@ def test_model_retrieve_deployment_config(
         mock_verify_model_region_and_return_specs: mock.Mock,
         mock_get_init_kwargs: mock.Mock,
     ):
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_verify_model_region_and_return_specs.side_effect = (
             lambda *args, **kwargs: get_base_spec_with_prototype_configs()
@@ -2179,7 +2267,7 @@ def test_model_display_benchmark_metrics(
         mock_verify_model_region_and_return_specs: mock.Mock,
         mock_get_init_kwargs: mock.Mock,
     ):
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_get_init_kwargs.side_effect = lambda *args, **kwargs: get_mock_init_kwargs(model_id)
         mock_verify_model_region_and_return_specs.side_effect = (
@@ -2217,7 +2305,7 @@ def test_model_benchmark_metrics(
         mock_verify_model_region_and_return_specs: mock.Mock,
         mock_get_init_kwargs: mock.Mock,
     ):
-        model_id, _ = "pytorch-eqa-bert-base-cased", "*"
+        model_id, _ = "pytorch-ic-mobilenet-v2", "*"
 
         mock_get_init_kwargs.side_effect = lambda *args, **kwargs: get_mock_init_kwargs(model_id)
         mock_verify_model_region_and_return_specs.side_effect = (
diff --git a/tests/unit/sagemaker/jumpstart/test_artifacts.py b/tests/unit/sagemaker/jumpstart/test_artifacts.py
index 3d9b5cef6a..e687a1c4ac 100644
--- a/tests/unit/sagemaker/jumpstart/test_artifacts.py
+++ b/tests/unit/sagemaker/jumpstart/test_artifacts.py
@@ -34,7 +34,7 @@
 from sagemaker.jumpstart.artifacts.model_uris import _retrieve_model_uri
 from sagemaker.jumpstart.enums import JumpStartScriptScope, JumpStartModelType
 
-from tests.unit.sagemaker.jumpstart.utils import get_spec_from_base_spec, get_special_model_spec
+from tests.unit.sagemaker.jumpstart.utils import get_special_model_spec
 from tests.unit.sagemaker.workflow.conftest import mock_client
 
 
@@ -220,12 +220,12 @@ def test_retrieve_training_artifact_key(self):
 @patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
 class RetrieveKwargsTest(unittest.TestCase):
 
-    model_id, model_version = "pytorch-eqa-bert-base-cased", "*"
+    model_id, model_version = "variant-model", "*"
     region = "us-west-2"
 
     def test_model_kwargs(self, patched_get_model_specs):
 
-        patched_get_model_specs.side_effect = get_spec_from_base_spec
+        patched_get_model_specs.side_effect = get_special_model_spec
 
         kwargs = artifacts._retrieve_model_init_kwargs(
             region=self.region,
@@ -242,7 +242,7 @@ def test_model_kwargs(self, patched_get_model_specs):
     def test_estimator_kwargs(self, patched_volume_size_supported, patched_get_model_specs):
 
         patched_volume_size_supported.return_value = False
-        patched_get_model_specs.side_effect = get_spec_from_base_spec
+        patched_get_model_specs.side_effect = get_special_model_spec
 
         kwargs = artifacts._retrieve_estimator_init_kwargs(
             region=self.region,
@@ -262,7 +262,7 @@ def test_estimator_kwargs_with_volume_size(
     ):
 
         patched_volume_size_supported.return_value = True
-        patched_get_model_specs.side_effect = get_spec_from_base_spec
+        patched_get_model_specs.side_effect = get_special_model_spec
 
         kwargs = artifacts._retrieve_estimator_init_kwargs(
             region=self.region,
@@ -282,7 +282,7 @@ def test_model_deploy_kwargs(self, patched_volume_size_supported, patched_get_mo
 
         patched_volume_size_supported.return_value = False
 
-        patched_get_model_specs.side_effect = get_spec_from_base_spec
+        patched_get_model_specs.side_effect = get_special_model_spec
 
         kwargs = artifacts._retrieve_model_deploy_kwargs(
             region=self.region,
@@ -300,7 +300,7 @@ def test_model_deploy_kwargs_with_volume_size(
 
         patched_volume_size_supported.return_value = True
 
-        patched_get_model_specs.side_effect = get_spec_from_base_spec
+        patched_get_model_specs.side_effect = get_special_model_spec
 
         kwargs = artifacts._retrieve_model_deploy_kwargs(
             region=self.region,
@@ -316,7 +316,7 @@ def test_model_deploy_kwargs_with_volume_size(
 
     def test_estimator_fit_kwargs(self, patched_get_model_specs):
 
-        patched_get_model_specs.side_effect = get_spec_from_base_spec
+        patched_get_model_specs.side_effect = get_special_model_spec
 
         kwargs = artifacts._retrieve_estimator_fit_kwargs(
             region=self.region,
diff --git a/tests/unit/sagemaker/jumpstart/test_notebook_utils.py b/tests/unit/sagemaker/jumpstart/test_notebook_utils.py
index 66e5777a7b..b1932b4ffc 100644
--- a/tests/unit/sagemaker/jumpstart/test_notebook_utils.py
+++ b/tests/unit/sagemaker/jumpstart/test_notebook_utils.py
@@ -48,7 +48,7 @@ def test_list_jumpstart_scripts(
     )
     patched_generate_jumpstart_models.side_effect = _generate_jumpstart_model_versions
     patched_read_s3_file.side_effect = lambda *args, **kwargs: json.dumps(
-        get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased").to_json()
+        get_prototype_model_spec(None, "pytorch-ic-mobilenet-v2").to_json()
     )
 
     assert list_jumpstart_scripts() == sorted(["inference", "training"])
@@ -109,7 +109,6 @@ def test_list_jumpstart_tasks(
     assert list_jumpstart_tasks() == sorted(
         [
             "classification",
-            "eqa",
             "ic",
             "semseg",
             "spc",
@@ -183,7 +182,6 @@ def test_list_jumpstart_frameworks(
             "huggingface",
             "lightgbm",
             "mxnet",
-            "pytorch",
             "sklearn",
             "xgboost",
         ]
@@ -220,7 +218,7 @@ def test_list_jumpstart_models_simple_case(
             ("huggingface-spc-bert-base-cased", "1.0.0"),
             ("lightgbm-classification-model", "1.0.0"),
             ("mxnet-semseg-fcn-resnet50-ade", "1.0.0"),
-            ("pytorch-eqa-bert-base-cased", "1.0.0"),
+            ("pytorch-ic-mobilenet-v2", "1.0.0"),
             ("sklearn-classification-linear", "1.0.0"),
             ("tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "1.0.0"),
             ("xgboost-classification-model", "1.0.0"),
@@ -236,7 +234,7 @@ def test_list_jumpstart_models_script_filter(
         self, patched_read_s3_file: Mock, patched_get_manifest: Mock
     ):
         patched_read_s3_file.side_effect = lambda *args, **kwargs: json.dumps(
-            get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased").to_json()
+            get_prototype_model_spec(None, "pytorch-ic-mobilenet-v2").to_json()
         )
         patched_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region)
@@ -269,7 +267,7 @@ def test_list_jumpstart_models_script_filter(
             ("huggingface-spc-bert-base-cased", "1.0.0"),
             ("lightgbm-classification-model", "1.0.0"),
             ("mxnet-semseg-fcn-resnet50-ade", "1.0.0"),
-            ("pytorch-eqa-bert-base-cased", "1.0.0"),
+            ("pytorch-ic-mobilenet-v2", "1.0.0"),
             ("sklearn-classification-linear", "1.0.0"),
             ("tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "1.0.0"),
             ("xgboost-classification-model", "1.0.0"),
@@ -326,7 +324,7 @@ def test_list_jumpstart_models_task_filter(
             ("huggingface-spc-bert-base-cased", "1.0.0"),
             ("lightgbm-classification-model", "1.0.0"),
             ("mxnet-semseg-fcn-resnet50-ade", "1.0.0"),
-            ("pytorch-eqa-bert-base-cased", "1.0.0"),
+            ("pytorch-ic-mobilenet-v2", "1.0.0"),
             ("sklearn-classification-linear", "1.0.0"),
             ("tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "1.0.0"),
             ("xgboost-classification-model", "1.0.0"),
@@ -349,7 +347,7 @@ def test_list_jumpstart_models_framework_filter(
         self, patched_read_s3_file: Mock, patched_get_manifest: Mock
     ):
         patched_read_s3_file.side_effect = lambda *args, **kwargs: json.dumps(
-            get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased").to_json()
+            get_prototype_model_spec(None, "pytorch-ic-mobilenet-v2").to_json()
         )
         patched_get_manifest.side_effect = lambda region, *args, **kwargs: get_prototype_manifest(
             region
@@ -387,7 +385,7 @@ def test_list_jumpstart_models_framework_filter(
             ("huggingface-spc-bert-base-cased", "1.0.0"),
             ("lightgbm-classification-model", "1.0.0"),
             ("mxnet-semseg-fcn-resnet50-ade", "1.0.0"),
-            ("pytorch-eqa-bert-base-cased", "1.0.0"),
+            ("pytorch-ic-mobilenet-v2", "1.0.0"),
             ("sklearn-classification-linear", "1.0.0"),
             ("xgboost-classification-model", "1.0.0"),
         ]
@@ -481,10 +479,10 @@ def get_manifest_more_versions(region: str = JUMPSTART_DEFAULT_REGION_NAME):
             ("mxnet-semseg-fcn-resnet50-ade", "2.5.1"),
             ("mxnet-semseg-fcn-resnet50-ade", "1.300.0"),
             ("mxnet-semseg-fcn-resnet50-ade", "1.4.0"),
-            ("pytorch-eqa-bert-base-cased", "2.400.0"),
-            ("pytorch-eqa-bert-base-cased", "2.5.1"),
-            ("pytorch-eqa-bert-base-cased", "1.300.0"),
-            ("pytorch-eqa-bert-base-cased", "1.4.0"),
+            ("pytorch-ic-mobilenet-v2", "2.400.0"),
+            ("pytorch-ic-mobilenet-v2", "2.5.1"),
+            ("pytorch-ic-mobilenet-v2", "1.300.0"),
+            ("pytorch-ic-mobilenet-v2", "1.4.0"),
             ("sklearn-classification-linear", "2.400.0"),
             ("sklearn-classification-linear", "2.5.1"),
             ("sklearn-classification-linear", "1.300.0"),
@@ -510,7 +508,7 @@ def get_manifest_more_versions(region: str = JUMPSTART_DEFAULT_REGION_NAME):
             ("huggingface-spc-bert-base-cased", "2.400.0"),
             ("lightgbm-classification-model", "2.400.0"),
             ("mxnet-semseg-fcn-resnet50-ade", "2.400.0"),
-            ("pytorch-eqa-bert-base-cased", "2.400.0"),
+            ("pytorch-ic-mobilenet-v2", "2.400.0"),
             ("sklearn-classification-linear", "2.400.0"),
             ("tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "2.400.0"),
             ("xgboost-classification-model", "2.400.0"),
@@ -536,12 +534,12 @@ def test_list_jumpstart_models_vulnerable_models(
         )
 
         def vulnerable_inference_model_spec(bucket, key, *args, **kwargs) -> str:
-            spec = get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased")
+            spec = get_prototype_model_spec(None, "catboost-classification-model")
             spec.inference_vulnerable = True
             return json.dumps(spec.to_json())
 
         def vulnerable_training_model_spec(bucket, key, *args, **kwargs):
-            spec = get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased")
+            spec = get_prototype_model_spec(None, "catboost-classification-model")
             spec.training_vulnerable = True
             return json.dumps(spec.to_json())
 
@@ -596,7 +594,7 @@ def test_list_jumpstart_models_deprecated_models(
         )
 
         def deprecated_model_spec(bucket, key, *args, **kwargs) -> str:
-            spec = get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased")
+            spec = get_prototype_model_spec(None, "pytorch-ic-mobilenet-v2")
             spec.deprecated = True
             return json.dumps(spec.to_json())
 
@@ -634,7 +632,7 @@ def test_list_jumpstart_models_no_versions(
             "huggingface-spc-bert-base-cased",
             "lightgbm-classification-model",
             "mxnet-semseg-fcn-resnet50-ade",
-            "pytorch-eqa-bert-base-cased",
+            "pytorch-ic-mobilenet-v2",
             "sklearn-classification-linear",
             "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1",
             "xgboost-classification-model",
@@ -668,7 +666,7 @@ def test_list_jumpstart_proprietary_models(
             "huggingface-spc-bert-base-cased",
             "lightgbm-classification-model",
             "mxnet-semseg-fcn-resnet50-ade",
-            "pytorch-eqa-bert-base-cased",
+            "pytorch-ic-mobilenet-v2",
             "sklearn-classification-linear",
             "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1",
             "xgboost-classification-model",
@@ -690,7 +688,7 @@ def test_list_jumpstart_models_complex_queries(
         patched_get_manifest: Mock,
     ):
         patched_read_s3_file.side_effect = lambda *args, **kwargs: json.dumps(
-            get_prototype_model_spec(None, "pytorch-eqa-bert-base-cased").to_json()
+            get_prototype_model_spec(None, "pytorch-ic-mobilenet-v2").to_json()
         )
         patched_get_manifest.side_effect = (
             lambda region, model_type, *args, **kwargs: get_prototype_manifest(region, model_type)
@@ -707,7 +705,7 @@ def test_list_jumpstart_models_complex_queries(
                 "false",
                 "unknown",
             )
-        ) == ["tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1"]
+        ) == ["pytorch-ic-mobilenet-v2", "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1"]
 
         assert list_jumpstart_models(
             Or(
@@ -716,7 +714,7 @@ def test_list_jumpstart_models_complex_queries(
                     "framework==tensorflow",
                     Identity(
                         And(
-                            And("incremental_training_supported==falSE"),
+                            And("incremental_training_supported==true"),
                             "true",
                             Or("unknown", "version equals 1.0.0"),
                         )
@@ -763,15 +761,15 @@ def test_get_model_url(
     region = "us-west-2"
     mock_session = Mock(s3_client=mock_client, boto_region_name=region)
 
-    model_id, version = "xgboost-classification-model", "1.0.0"
-    assert "https://xgboost.readthedocs.io/en/latest/" == get_model_url(model_id, version)
+    model_id, version = "xgboost-classification-model", "*"
+    assert "https://xgboost.readthedocs.io/en/release_1.7.0/" == get_model_url(model_id, version)
 
     model_id, version = "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "1.0.0"
     assert "https://tfhub.dev/google/bit/m-r101x1/ilsvrc2012_classification/1" == get_model_url(
         model_id, version
     )
 
-    model_id, version = "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "1.0.0"
+    model_id, version = "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1", "*"
 
     patched_get_model_specs.reset_mock()
     patched_get_model_specs.side_effect = lambda *largs, **kwargs: get_prototype_model_spec(
diff --git a/tests/unit/sagemaker/jumpstart/test_types.py b/tests/unit/sagemaker/jumpstart/test_types.py
index 884639b5d6..3efa8c8c81 100644
--- a/tests/unit/sagemaker/jumpstart/test_types.py
+++ b/tests/unit/sagemaker/jumpstart/test_types.py
@@ -344,65 +344,86 @@ def test_jumpstart_model_specs():
     specs1 = JumpStartModelSpecs(BASE_SPEC)
 
     assert specs1.model_id == "pytorch-ic-mobilenet-v2"
-    assert specs1.version == "1.0.0"
-    assert specs1.min_sdk_version == "2.49.0"
+    assert specs1.version == "3.0.6"
+    assert specs1.min_sdk_version == "2.189.0"
     assert specs1.training_supported
     assert specs1.incremental_training_supported
     assert specs1.hosting_ecr_specs == JumpStartECRSpecs(
         {
             "framework": "pytorch",
-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework_version": "1.10.0",
+            "py_version": "py38",
         }
     )
     assert specs1.training_ecr_specs == JumpStartECRSpecs(
         {
             "framework": "pytorch",
-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework_version": "1.10.0",
+            "py_version": "py38",
         }
     )
-    assert specs1.hosting_artifact_key == "pytorch-infer/infer-pytorch-ic-mobilenet-v2.tar.gz"
-    assert specs1.training_artifact_key == "pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz"
+    assert (
+        specs1.hosting_artifact_key
+        == "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference/v2.0.0/"
+    )
+    assert (
+        specs1.training_artifact_key
+        == "pytorch-training/v2.0.0/train-pytorch-ic-mobilenet-v2.tar.gz"
+    )
     assert (
         specs1.hosting_script_key
-        == "source-directory-tarballs/pytorch/inference/ic/v1.0.0/sourcedir.tar.gz"
+        == "source-directory-tarballs/pytorch/inference/ic/v2.0.0/sourcedir.tar.gz"
     )
     assert (
         specs1.training_script_key
-        == "source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz"
+        == "source-directory-tarballs/pytorch/transfer_learning/ic/v2.3.0/sourcedir.tar.gz"
     )
     assert specs1.hyperparameters == [
+        JumpStartHyperparameter(
+            {
+                "name": "train_only_top_layer",
+                "type": "text",
+                "options": ["True", "False"],
+                "default": "True",
+                "scope": "algorithm",
+            }
+        ),
         JumpStartHyperparameter(
             {
                 "name": "epochs",
                 "type": "int",
-                # "_is_hub_content": False,
-                "default": 3,
+                "default": 5,
+                "scope": "algorithm",
                 "min": 1,
                 "max": 1000,
-                "scope": "algorithm",
             }
         ),
         JumpStartHyperparameter(
             {
-                "name": "adam-learning-rate",
+                "name": "learning_rate",
                 "type": "float",
-                # "_is_hub_content": False,
-                "default": 0.05,
+                "default": 0.001,
+                "scope": "algorithm",
                 "min": 1e-08,
                 "max": 1,
-                "scope": "algorithm",
             }
         ),
         JumpStartHyperparameter(
             {
-                "name": "batch-size",
+                "name": "batch_size",
                 "type": "int",
-                # "_is_hub_content": False,
                 "default": 4,
+                "scope": "algorithm",
                 "min": 1,
                 "max": 1024,
+            }
+        ),
+        JumpStartHyperparameter(
+            {
+                "name": "reinitialize_top_layer",
+                "type": "text",
+                "options": ["Auto", "True", "False"],
+                "default": "Auto",
                 "scope": "algorithm",
             }
         ),
@@ -410,7 +431,6 @@ def test_jumpstart_model_specs():
             {
                 "name": "sagemaker_submit_directory",
                 "type": "text",
-                # "_is_hub_content": False,
                 "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
                 "scope": "container",
             }
@@ -419,7 +439,6 @@ def test_jumpstart_model_specs():
             {
                 "name": "sagemaker_program",
                 "type": "text",
-                # "_is_hub_content": False,
                 "default": "transfer_learning.py",
                 "scope": "container",
             }
@@ -428,13 +447,13 @@ def test_jumpstart_model_specs():
             {
                 "name": "sagemaker_container_log_level",
                 "type": "text",
-                # "_is_hub_content": False,
                 "default": "20",
                 "scope": "container",
             }
         ),
     ]
 
+    print(specs1.to_json())
     assert specs1.to_json() == BASE_SPEC
 
     BASE_SPEC_COPY = copy.deepcopy(BASE_SPEC)
@@ -993,8 +1012,8 @@ def test_inference_configs_parsing():
 
     # Non-overrided fields in top config
     assert specs1.model_id == "pytorch-ic-mobilenet-v2"
-    assert specs1.version == "1.0.0"
-    assert specs1.min_sdk_version == "2.49.0"
+    assert specs1.version == "3.0.6"
+    assert specs1.min_sdk_version == "2.189.0"
     assert specs1.training_supported
     assert specs1.incremental_training_supported
     assert specs1.hosting_ecr_specs == JumpStartECRSpecs(
@@ -1007,51 +1026,72 @@ def test_inference_configs_parsing():
     assert specs1.training_ecr_specs == JumpStartECRSpecs(
         {
             "framework": "pytorch",
-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework_version": "1.10.0",
+            "py_version": "py38",
         }
     )
     assert (
         specs1.hosting_artifact_key
         == "artifacts/meta-textgeneration-llama-2-7b/neuron-inference/model/"
     )
-    assert specs1.training_artifact_key == "pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz"
+    assert (
+        specs1.training_artifact_key
+        == "pytorch-training/v2.0.0/train-pytorch-ic-mobilenet-v2.tar.gz"
+    )
     assert (
         specs1.hosting_script_key
-        == "source-directory-tarballs/pytorch/inference/ic/v1.0.0/sourcedir.tar.gz"
+        == "source-directory-tarballs/pytorch/inference/ic/v2.0.0/sourcedir.tar.gz"
     )
     assert (
         specs1.training_script_key
-        == "source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz"
+        == "source-directory-tarballs/pytorch/transfer_learning/ic/v2.3.0/sourcedir.tar.gz"
     )
     assert specs1.hyperparameters == [
+        JumpStartHyperparameter(
+            {
+                "name": "train_only_top_layer",
+                "type": "text",
+                "options": ["True", "False"],
+                "default": "True",
+                "scope": "algorithm",
+            }
+        ),
         JumpStartHyperparameter(
             {
                 "name": "epochs",
                 "type": "int",
-                "default": 3,
+                "default": 5,
+                "scope": "algorithm",
                 "min": 1,
                 "max": 1000,
-                "scope": "algorithm",
             }
         ),
         JumpStartHyperparameter(
             {
-                "name": "adam-learning-rate",
+                "name": "learning_rate",
                 "type": "float",
-                "default": 0.05,
+                "default": 0.001,
+                "scope": "algorithm",
                 "min": 1e-08,
                 "max": 1,
-                "scope": "algorithm",
             }
         ),
         JumpStartHyperparameter(
             {
-                "name": "batch-size",
+                "name": "batch_size",
                 "type": "int",
                 "default": 4,
+                "scope": "algorithm",
                 "min": 1,
                 "max": 1024,
+            }
+        ),
+        JumpStartHyperparameter(
+            {
+                "name": "reinitialize_top_layer",
+                "type": "text",
+                "options": ["Auto", "True", "False"],
+                "default": "Auto",
                 "scope": "algorithm",
             }
         ),
@@ -1255,62 +1295,86 @@ def test_training_configs_parsing():
     # Non-overrided fields in top config
     # By default training config is not applied to model spec
     assert specs1.model_id == "pytorch-ic-mobilenet-v2"
-    assert specs1.version == "1.0.0"
-    assert specs1.min_sdk_version == "2.49.0"
+    assert specs1.version == "3.0.6"
+    assert specs1.min_sdk_version == "2.189.0"
     assert specs1.training_supported
     assert specs1.incremental_training_supported
     assert specs1.hosting_ecr_specs == JumpStartECRSpecs(
         {
             "framework": "pytorch",
-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework_version": "1.10.0",
+            "py_version": "py38",
         }
     )
     assert specs1.training_ecr_specs == JumpStartECRSpecs(
         {
             "framework": "pytorch",
-            "framework_version": "1.5.0",
-            "py_version": "py3",
+            "framework_version": "1.10.0",
+            "py_version": "py38",
         }
     )
-    assert specs1.hosting_artifact_key == "pytorch-infer/infer-pytorch-ic-mobilenet-v2.tar.gz"
-    assert specs1.training_artifact_key == "pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz"
+    assert (
+        specs1.hosting_artifact_key
+        == "pytorch-ic/pytorch-ic-mobilenet-v2/artifacts/inference/v2.0.0/"
+    )
+    assert (
+        specs1.training_artifact_key
+        == "pytorch-training/v2.0.0/train-pytorch-ic-mobilenet-v2.tar.gz"
+    )
     assert (
         specs1.hosting_script_key
-        == "source-directory-tarballs/pytorch/inference/ic/v1.0.0/sourcedir.tar.gz"
+        == "source-directory-tarballs/pytorch/inference/ic/v2.0.0/sourcedir.tar.gz"
     )
     assert (
         specs1.training_script_key
-        == "source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz"
+        == "source-directory-tarballs/pytorch/transfer_learning/ic/v2.3.0/sourcedir.tar.gz"
     )
     assert specs1.hyperparameters == [
+        JumpStartHyperparameter(
+            {
+                "name": "train_only_top_layer",
+                "type": "text",
+                "options": ["True", "False"],
+                "default": "True",
+                "scope": "algorithm",
+            }
+        ),
         JumpStartHyperparameter(
             {
                 "name": "epochs",
                 "type": "int",
-                "default": 3,
+                "default": 5,
+                "scope": "algorithm",
                 "min": 1,
                 "max": 1000,
-                "scope": "algorithm",
             }
         ),
         JumpStartHyperparameter(
             {
-                "name": "adam-learning-rate",
+                "name": "learning_rate",
                 "type": "float",
-                "default": 0.05,
+                "default": 0.001,
+                "scope": "algorithm",
                 "min": 1e-08,
                 "max": 1,
-                "scope": "algorithm",
             }
         ),
         JumpStartHyperparameter(
             {
-                "name": "batch-size",
+                "name": "batch_size",
                 "type": "int",
                 "default": 4,
+                "scope": "algorithm",
                 "min": 1,
                 "max": 1024,
+            }
+        ),
+        JumpStartHyperparameter(
+            {
+                "name": "reinitialize_top_layer",
+                "type": "text",
+                "options": ["Auto", "True", "False"],
+                "default": "Auto",
                 "scope": "algorithm",
             }
         ),
@@ -1477,11 +1541,9 @@ def test_set_training_config():
     specs1 = JumpStartModelSpecs(spec)
 
     assert specs1.supported_training_instance_types == [
-        "ml.p3.2xlarge",
-        "ml.p2.xlarge",
-        "ml.g4dn.2xlarge",
         "ml.m5.xlarge",
         "ml.c5.2xlarge",
+        "ml.m4.xlarge",
     ]
     specs1.set_config("gpu-training-budget", scope=JumpStartScriptScope.TRAINING)
 
diff --git a/tests/unit/sagemaker/jumpstart/test_utils.py b/tests/unit/sagemaker/jumpstart/test_utils.py
index d228b4450e..7cf8fdc9b6 100644
--- a/tests/unit/sagemaker/jumpstart/test_utils.py
+++ b/tests/unit/sagemaker/jumpstart/test_utils.py
@@ -1364,7 +1364,7 @@ def test_validate_model_id_and_get_type_invalid(
             )
 
             assert (
-                utils.validate_model_id_and_get_type("pytorch-eqa-bert-base-cased")
+                utils.validate_model_id_and_get_type("pytorch-ic-mobilenet-v2")
                 == JumpStartModelType.OPEN_WEIGHTS
             )
             mock_get_manifest.assert_called_with(
diff --git a/tests/unit/sagemaker/model_uris/jumpstart/test_common.py b/tests/unit/sagemaker/model_uris/jumpstart/test_common.py
index e71207d439..8593c599fe 100644
--- a/tests/unit/sagemaker/model_uris/jumpstart/test_common.py
+++ b/tests/unit/sagemaker/model_uris/jumpstart/test_common.py
@@ -184,4 +184,7 @@ def test_jumpstart_artifact_bucket_override(
         model_id="pytorch-ic-mobilenet-v2",
         model_version="*",
     )
-    assert uri == "s3://some-cool-bucket-name/pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz"
+    assert (
+        uri
+        == "s3://some-cool-bucket-name/pytorch-training/v2.0.0/train-pytorch-ic-mobilenet-v2.tar.gz"
+    )
diff --git a/tests/unit/sagemaker/script_uris/jumpstart/test_common.py b/tests/unit/sagemaker/script_uris/jumpstart/test_common.py
index b67f238cac..6c4d6b688f 100644
--- a/tests/unit/sagemaker/script_uris/jumpstart/test_common.py
+++ b/tests/unit/sagemaker/script_uris/jumpstart/test_common.py
@@ -185,6 +185,6 @@ def test_jumpstart_artifact_bucket_override(
         model_version="*",
     )
     assert (
-        uri
-        == "s3://some-cool-bucket-name/source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz"
+        uri == "s3://some-cool-bucket-name/source-directory-tarballs/pytorch/"
+        "transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz"
     )
diff --git a/tests/unit/sagemaker/script_uris/jumpstart/test_pytorch.py b/tests/unit/sagemaker/script_uris/jumpstart/test_pytorch.py
index d62db7a785..80f2449901 100644
--- a/tests/unit/sagemaker/script_uris/jumpstart/test_pytorch.py
+++ b/tests/unit/sagemaker/script_uris/jumpstart/test_pytorch.py
@@ -29,22 +29,22 @@ def test_jumpstart_pytorch_script_uri(patched_get_model_specs):
     uri = script_uris.retrieve(
         region="us-west-2",
         script_scope="inference",
-        model_id="pytorch-eqa-bert-base-cased",
+        model_id="pytorch-ic-mobilenet-v2",
         model_version="*",
     )
     assert (
-        uri == "s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/pytorch/"
-        "inference/eqa/v1.0.0/sourcedir.tar.gz"
+        uri
+        == "s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/pytorch/inference/ic/v2.0.0/sourcedir.tar.gz"
     )
 
     # training
     uri = script_uris.retrieve(
         region="us-west-2",
         script_scope="training",
-        model_id="pytorch-eqa-bert-base-cased",
+        model_id="pytorch-ic-mobilenet-v2",
         model_version="*",
     )
     assert (
-        uri == "s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/pytorch/"
-        "transfer_learning/eqa/v1.0.0/sourcedir.tar.gz"
+        uri == "s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/"
+        "pytorch/transfer_learning/ic/prepack/v1.1.0/sourcedir.tar.gz"
     )