lint

Former-commit-id: 6b1f89b6494e9b6b087fe90600617a3024e014e5

src/llmtuner/hparams/data_args.py

@@ -7,6 +7,7 @@ class DataArguments:
     r"""
     Arguments pertaining to what data we are going to input our model for training and evaluation.
     """
+
     template: Optional[str] = field(
         default=None, metadata={"help": "Which template to use for constructing prompts in training and inference."}
     )

src/llmtuner/hparams/evaluation_args.py

@@ -10,6 +10,7 @@ class EvaluationArguments:
     r"""
     Arguments pertaining to specify the evaluation parameters.
     """
+
     task: str = field(metadata={"help": "Name of the evaluation task."})
     task_dir: Optional[str] = field(
         default="evaluation", metadata={"help": "Path to the folder containing the evaluation datasets."}

src/llmtuner/hparams/finetuning_args.py

@@ -8,6 +8,7 @@ class FreezeArguments:
     r"""
     Arguments pertaining to the freeze (partial-parameter) training.
     """
+
     name_module_trainable: Optional[str] = field(
         default="mlp",
         metadata={
@@ -31,6 +32,7 @@ class LoraArguments:
     r"""
     Arguments pertaining to the LoRA training.
     """
+
     additional_target: Optional[str] = field(
         default=None,
         metadata={
@@ -67,6 +69,7 @@ class RLHFArguments:
     r"""
     Arguments pertaining to the PPO and DPO training.
     """
+
     dpo_beta: Optional[float] = field(default=0.1, metadata={"help": "The beta parameter for the DPO loss."})
     dpo_loss: Optional[Literal["sigmoid", "hinge", "ipo", "kto"]] = field(
         default="sigmoid", metadata={"help": "The type of DPO loss to use."}
@@ -122,6 +125,7 @@ class FinetuningArguments(FreezeArguments, LoraArguments, RLHFArguments):
     r"""
     Arguments pertaining to which techniques we are going to fine-tuning with.
     """
+
     stage: Optional[Literal["pt", "sft", "rm", "ppo", "dpo"]] = field(
         default="sft", metadata={"help": "Which stage will be performed in training."}
     )

src/llmtuner/hparams/generating_args.py

@@ -7,6 +7,7 @@ class GeneratingArguments:
     r"""
     Arguments pertaining to specify the decoding parameters.
     """
+
     do_sample: Optional[bool] = field(
         default=True, metadata={"help": "Whether or not to use sampling, use greedy decoding otherwise."}
     )

src/llmtuner/hparams/model_args.py

@@ -7,6 +7,7 @@ class ModelArguments:
     r"""
     Arguments pertaining to which model/config/tokenizer we are going to fine-tune.
     """
+
     model_name_or_path: str = field(
         metadata={"help": "Path to the model weight or identifier from huggingface.co/models or modelscope.cn/models."}
     )