[misc] upgrade cli (#7714)

src/llamafactory/hparams/parser.py

@@ -390,8 +390,10 @@ def get_train_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _
 def get_infer_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _INFER_CLS:
     model_args, data_args, finetuning_args, generating_args = _parse_infer_args(args)
 
+    # Setup logging
     _set_transformers_logging()
 
+    # Check arguments
     if model_args.infer_backend == "vllm":
         if finetuning_args.stage != "sft":
             raise ValueError("vLLM engine only supports auto-regressive models.")
@@ -408,6 +410,7 @@ def get_infer_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _
     _verify_model_args(model_args, data_args, finetuning_args)
     _check_extra_dependencies(model_args, finetuning_args)
 
+    # Post-process model arguments
     if model_args.export_dir is not None and model_args.export_device == "cpu":
         model_args.device_map = {"": torch.device("cpu")}
         if data_args.cutoff_len != DataArguments().cutoff_len:  # override cutoff_len if it is not default
@@ -421,8 +424,10 @@ def get_infer_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _
 def get_eval_args(args: Optional[Union[dict[str, Any], list[str]]] = None) -> _EVAL_CLS:
     model_args, data_args, eval_args, finetuning_args = _parse_eval_args(args)
 
+    # Setup logging
     _set_transformers_logging()
 
+    # Check arguments
     if model_args.infer_backend == "vllm":
         raise ValueError("vLLM backend is only available for API, CLI and Web.")