update requirements

requirements.txt

@@ -1,9 +1,10 @@
 torch>=1.13.1
-transformers>=4.31.0
+transformers>=4.31.0,<4.35.0
 datasets>=2.12.0
 accelerate>=0.21.0
 peft>=0.4.0
 trl>=0.7.2
+gradio>=3.38.0,<4.0.0
 scipy
 sentencepiece
 protobuf
@@ -12,9 +13,8 @@ fire
 jieba
 rouge-chinese
 nltk
-gradio==3.50.2
 uvicorn
-pydantic==1.10.11
-fastapi==0.95.1
+pydantic
+fastapi
 sse-starlette
 matplotlib

src/llmtuner/api/app.py

@@ -32,9 +32,9 @@ async def lifespan(app: FastAPI): # collects GPU memory
 
 
 def to_json(data: BaseModel) -> str:
-    try:
+    try: # pydantic v2
         return json.dumps(data.model_dump(exclude_unset=True), ensure_ascii=False)
-    except:
+    except: # pydantic v1
         return data.json(exclude_unset=True, ensure_ascii=False)
 
 

src/llmtuner/tuner/core/loader.py

@@ -14,7 +14,6 @@ from transformers import (
     PreTrainedTokenizerBase
 )
 from transformers.models.llama import modeling_llama as LlamaModule
-from transformers.utils import check_min_version
 from transformers.utils.versions import require_version
 from trl import AutoModelForCausalLMWithValueHead
 
@@ -39,7 +38,7 @@ if TYPE_CHECKING:
 logger = get_logger(__name__)
 
 
-check_min_version("4.31.0")
+require_version("transformers>=4.31.0,<4.35.0", "To fix: pip install \"transformers>=4.31.0,<4.35.0\"")
 require_version("datasets>=2.12.0", "To fix: pip install datasets>=2.12.0")
 require_version("accelerate>=0.21.0", "To fix: pip install accelerate>=0.21.0")
 require_version("peft>=0.4.0", "To fix: pip install peft>=0.4.0")

src/llmtuner/webui/interface.py

@@ -14,7 +14,7 @@ from llmtuner.webui.css import CSS
 from llmtuner.webui.engine import Engine
 
 
-require_version("gradio==3.50.2", "To fix: pip install gradio==3.50.2")
+require_version("gradio>=3.38.0,<4.0.0", "To fix: pip install \"gradio>=3.38.0,<4.0.0\"")
 
 
 def create_ui() -> gr.Blocks: