model integration with DT - revised

Author: kshitij-microsoft

src/machinelearningservices/CHANGELOG.rst

@@ -1,3 +1,9 @@
+## 2025-12-19
+
+### Azure Machine Learning CLI (v2) v 2.41.0
+- `az ml model create`
+  - Add support for `default_deployment_template` parameter to associate a deployment template with a model.
+
 ## 2025-11-04
 
 ### Azure Machine Learning CLI (v2) v 2.40.0

src/machinelearningservices/azext_mlv2/manual/_help/_model_help.py

@@ -40,6 +40,8 @@ def get_model_help():
           text: az ml model create --name my-model --version 1 --path azureml://jobs/c42d2507-4953-4a7c-a4c1-2b5bfe0ac64e/outputs/artifacts/paths/model/ --resource-group my-resource-group --workspace-name my-workspace
         - name: Create a model from a datastore 'azureml://datastores/<datastore-name>/paths/<path-to-model-relative-to-the-root-of-the-datastore-location>' using command options
           text: az ml model create --name my-model --version 1 --path azureml://datastores/myblobstore/paths/models/cifar10/cifar.pt --resource-group my-resource-group --workspace-name my-workspace
+        - name: Create a model from a YAML file and override the default deployment template
+          text: az ml model create --registry-name my-registry --resource-group my-resource-group --file model.yaml --set default_deployment_template.asset_id="azureml://registries/my-registry/deploymenttemplates/my-template/versions/1" --version 3
     """
     helps[
         "ml model show"

src/machinelearningservices/azext_mlv2/manual/_params/_model_params.py

@@ -64,7 +64,8 @@ def load_model_params(self):
         c.argument(
             "default_deployment_template",
             options_list=["--default-deployment-template"],
-            help="Default deployment template for the model.",
+            help="Default deployment template for the model. Can be overridden using --set with the format: "
+                 "--set default_deployment_template.asset_id=\"azureml://registries/<registry-name>/deploymenttemplates/<template-name>/versions/<version>\"",
         )
 
     with self.argument_context("ml model show") as c:

src/machinelearningservices/azext_mlv2/manual/custom/model.py

@@ -62,6 +62,8 @@ def ml_model_create(
         params_override.append({"stage": stage})
     if datastore:
         params_override.append({"datastore": datastore})
+    if default_deployment_template:
+        params_override.append({"default_deployment_template": default_deployment_template})
 
     model_info = ModelInfo()
     try: