Merge pull request #254 from stochasticai/dev

release 0.1.8

Author: MarcosRiveraMartinez

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "xturing"
-version = "0.1.7"
+version = "0.1.8"
 description = "Fine-tuning, evaluation and data generation for LLMs"
 
 authors = [
@@ -43,12 +43,12 @@ keywords = [
 dependencies = [
     "torch >= 1.9.0",
     "pytorch-lightning",
-    "transformers==4.28.1",
-    "datasets",
-    "evaluate",
-    "bitsandbytes==0.37.2",
+    "transformers==4.31.0",
+    "datasets==2.14.5",
+    "evaluate==0.4.0",
+    "bitsandbytes==0.41.1",
     "sentencepiece",
-    "deepspeed",
+    "deepspeed==0.9.5",
     "gradio",
     "click",
     "wget",
@@ -58,7 +58,7 @@ dependencies = [
     "openai >= 0.27.0",
     "pydantic >= 1.10.0",
     "rouge-score >= 0.1.2",
-    "accelerate",
+    "accelerate==0.22.0",
     "wandb",
 ]
 

src/xturing/__about__.py

@@ -1 +1 @@
-__version__ = "0.1.7"
+__version__ = "0.1.8"

src/xturing/config/finetuning_config.yaml

@@ -32,6 +32,13 @@ bloom_lora_int8:
   batch_size: 8
   max_length: 256
 
+bloom_int8:
+  learning_rate: 1e-4
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 8
+  max_length: 256
+
 cerebras:
   learning_rate: 5e-5
   weight_decay: 0.01
@@ -50,6 +57,13 @@ cerebras_lora_int8:
   batch_size: 8
   max_length: 256
 
+cerebras_int8:
+  learning_rate: 1e-4
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 8
+  max_length: 256
+
 distilgpt2:
   learning_rate: 1e-3
   weight_decay: 0.01
@@ -115,6 +129,13 @@ galactica_lora_int8:
   batch_size: 8
   max_length: 256
 
+galactica_int8:
+  learning_rate: 1e-4
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 8
+  max_length: 256
+
 generic:
   learning_rate: 1e-4
   weight_decay: 0.01
@@ -169,6 +190,13 @@ gptj_lora_int8:
   batch_size: 8
   max_length: 256
 
+gptj_int8:
+  learning_rate: 1e-4
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 8
+  max_length: 256
+
 gpt2:
   learning_rate: 1e-3
   weight_decay: 0.01
@@ -187,13 +215,18 @@ gpt2_lora_int8:
   num_train_epochs: 3
   batch_size: 16
 
+gpt2_int8:
+  learning_rate: 3e-3
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 16
+
 llama:
   learning_rate: 5e-5
   weight_decay: 0.01
   num_train_epochs: 3
   optimizer_name: cpu_adam
 
-
 llama_lora:
   learning_rate: 1e-4
   weight_decay: 0.01
@@ -207,6 +240,13 @@ llama_lora_int8:
   batch_size: 8
   max_length: 256
 
+llama_int8:
+  learning_rate: 1e-4
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 8
+  max_length: 256
+
 llama_lora_kbit:
   learning_rate: 3e-4
   num_train_epochs: 3
@@ -275,3 +315,10 @@ opt_lora_int8:
   num_train_epochs: 3
   batch_size: 8
   max_length: 256
+
+opt_int8:
+  learning_rate: 1e-4
+  weight_decay: 0.01
+  num_train_epochs: 3
+  batch_size: 8
+  max_length: 256

src/xturing/config/generation_config.yaml

@@ -25,6 +25,11 @@ bloom_lora_int8:
   max_new_tokens: 256
   do_sample: false
 
+# Greedy search
+bloom_int8:
+  max_new_tokens: 256
+  do_sample: false
+
 # Contrastive search
 cerebras:
   penalty_alpha: 0.6
@@ -44,6 +49,11 @@ cerebras_lora_int8:
   max_new_tokens: 256
   do_sample: false
 
+# Greedy search
+cerebras_int8:
+  max_new_tokens: 256
+  do_sample: false
+
 # Top-p sampling
 distilgpt2:
   do_sample: true
@@ -102,6 +112,11 @@ galactica_lora_int8:
   max_new_tokens: 256
   do_sample: false
 
+# Greedy search
+galactica_int8:
+  max_new_tokens: 256
+  do_sample: false
+
 # Greedy search
 generic:
   max_new_tokens: 256
@@ -146,6 +161,11 @@ gptj_lora_int8:
   max_new_tokens: 256
   do_sample: false
 
+# Greedy search
+gptj_int8:
+  max_new_tokens: 256
+  do_sample: false
+
 # Top-p sampling
 gpt2:
   do_sample: true
@@ -167,6 +187,13 @@ gpt2_lora_int8:
   top_p: 0.92
   max_new_tokens: 256
 
+# Top-p sampling
+gpt2_int8:
+  do_sample: true
+  top_k: 0
+  top_p: 0.92
+  max_new_tokens: 256
+
 # Contrastive search
 llama:
   penalty_alpha: 0.6
@@ -186,6 +213,11 @@ llama_lora_int8:
   max_new_tokens: 256
   do_sample: false
 
+# Greedy search
+llama_int8:
+  max_new_tokens: 256
+  do_sample: false
+
 # Greedy search
 llama_lora_kbit:
   max_new_tokens: 256
@@ -238,3 +270,8 @@ opt_lora:
 opt_lora_int8:
   max_new_tokens: 256
   do_sample: false
+
+# Greedy search
+opt_int8:
+  max_new_tokens: 256
+  do_sample: false

src/xturing/engines/__init__.py

@@ -44,7 +44,13 @@
     GPTJLoraEngine,
     GPTJLoraInt8Engine,
 )
-from xturing.engines.llama2_engine import LLama2Engine
+from xturing.engines.llama2_engine import (
+    LLama2Engine,
+    LLama2Int8Engine,
+    LLama2LoraEngine,
+    LLama2LoraInt8Engine,
+    LLama2LoraKbitEngine,
+)
 from xturing.engines.llama_engine import (
     LLamaEngine,
     LLamaInt8Engine,
@@ -97,6 +103,10 @@
 BaseEngine.add_to_registry(LlamaLoraInt8Engine.config_name, LlamaLoraInt8Engine)
 BaseEngine.add_to_registry(LlamaLoraKbitEngine.config_name, LlamaLoraKbitEngine)
 BaseEngine.add_to_registry(LLama2Engine.config_name, LLama2Engine)
+BaseEngine.add_to_registry(LLama2Int8Engine.config_name, LLama2Int8Engine)
+BaseEngine.add_to_registry(LLama2LoraEngine.config_name, LLama2LoraEngine)
+BaseEngine.add_to_registry(LLama2LoraInt8Engine.config_name, LLama2LoraInt8Engine)
+BaseEngine.add_to_registry(LLama2LoraKbitEngine.config_name, LLama2LoraKbitEngine)
 BaseEngine.add_to_registry(OPTEngine.config_name, OPTEngine)
 BaseEngine.add_to_registry(OPTInt8Engine.config_name, OPTInt8Engine)
 BaseEngine.add_to_registry(OPTLoraEngine.config_name, OPTLoraEngine)

src/xturing/engines/generic_engine.py

@@ -64,7 +64,7 @@ def __init__(
 
 
 class GenericLoraKbitEngine(CausalLoraKbitEngine):
-    config_name: str = "generic+lora_kbit_engine"
+    config_name: str = "generic_lora_kbit_engine"
 
     def __init__(
         self,
@@ -75,7 +75,6 @@ def __init__(
         super().__init__(
             model_name=model_name,
             weights_path=weights_path,
-            load_4bit=True,
             target_modules=target_modules,
         )
 

src/xturing/models/__init__.py

@@ -36,7 +36,13 @@
     LlamaLoraInt8,
     LlamaLoraKbit,
 )
-from xturing.models.llama2 import Llama2
+from xturing.models.llama2 import (
+    Llama2,
+    Llama2Int8,
+    Llama2Lora,
+    Llama2LoraInt8,
+    Llama2LoraKbit,
+)
 from xturing.models.opt import OPT, OPTInt8, OPTLora, OPTLoraInt8
 from xturing.models.stable_diffusion import StableDiffusion
 
@@ -78,6 +84,10 @@
 BaseModel.add_to_registry(LlamaLoraInt8.config_name, LlamaLoraInt8)
 BaseModel.add_to_registry(LlamaLoraKbit.config_name, LlamaLoraKbit)
 BaseModel.add_to_registry(Llama2.config_name, Llama2)
+BaseModel.add_to_registry(Llama2Int8.config_name, Llama2Int8)
+BaseModel.add_to_registry(Llama2Lora.config_name, Llama2Lora)
+BaseModel.add_to_registry(Llama2LoraInt8.config_name, Llama2LoraInt8)
+BaseModel.add_to_registry(Llama2LoraKbit.config_name, Llama2LoraKbit)
 BaseModel.add_to_registry(OPT.config_name, OPT)
 BaseModel.add_to_registry(OPTInt8.config_name, OPTInt8)
 BaseModel.add_to_registry(OPTLora.config_name, OPTLora)