support full-parameter PPO

Former-commit-id: 4af967d69475e1c9fdf1a7983cd6b83bd431abff

src/llmtuner/hparams/model_args.py

@@ -54,22 +54,10 @@ class ModelArguments:
         default=False,
         metadata={"help": "Enable shift short attention (S^2-Attn) proposed by LongLoRA."}
     )
-    reward_model: Optional[str] = field( # TODO: move it to FinetuningArguments
-        default=None,
-        metadata={"help": "Path to the directory containing the checkpoints of the reward model."}
-    )
-    plot_loss: Optional[bool] = field( # TODO: move it to FinetuningArguments
-        default=False,
-        metadata={"help": "Whether to plot the training loss after fine-tuning or not."}
-    )
     hf_hub_token: Optional[str] = field(
         default=None,
         metadata={"help": "Auth token to log in with Hugging Face Hub."}
     )
-    export_dir: Optional[str] = field(
-        default=None,
-        metadata={"help": "Path to the directory to save the exported model."}
-    )
 
     def __post_init__(self):
         self.compute_dtype = None
@@ -81,8 +69,7 @@ class ModelArguments:
         if self.checkpoint_dir is not None: # support merging multiple lora weights
             self.checkpoint_dir = [cd.strip() for cd in self.checkpoint_dir.split(",")]
 
-        if self.quantization_bit is not None:
-            assert self.quantization_bit in [4, 8], "We only accept 4-bit or 8-bit quantization."
+        assert self.quantization_bit in [None, 8, 4], "We only accept 4-bit or 8-bit quantization."
 
     def to_dict(self) -> Dict[str, Any]:
         return asdict(self)