refactor export, fix #1190

Former-commit-id: 30e60e37023a7c4a2db033ffec0542efa3d5cdfb

src/llmtuner/hparams/model_args.py

@@ -46,6 +46,10 @@ class ModelArguments:
         default=None,
         metadata={"help": "Adopt scaled rotary positional embeddings."}
     )
+    checkpoint_dir: Optional[str] = field(
+        default=None,
+        metadata={"help": "Path to the directory(s) containing the delta model checkpoints as well as the configurations."}
+    )
     flash_attn: Optional[bool] = field(
         default=False,
         metadata={"help": "Enable FlashAttention-2 for faster training."}
@@ -54,14 +58,14 @@ class ModelArguments:
         default=False,
         metadata={"help": "Enable shift short attention (S^2-Attn) proposed by LongLoRA."}
     )
-    checkpoint_dir: Optional[str] = field(
-        default=None,
-        metadata={"help": "Path to the directory(s) containing the delta model checkpoints as well as the configurations."}
-    )
     reward_model: Optional[str] = field(
         default=None,
         metadata={"help": "Path to the directory containing the checkpoints of the reward model."}
     )
+    upcast_layernorm: Optional[bool] = field(
+        default=False,
+        metadata={"help": "Whether to upcast the layernorm weights in fp32."}
+    )
     plot_loss: Optional[bool] = field(
         default=False,
         metadata={"help": "Whether to plot the training loss after fine-tuning or not."}
@@ -70,9 +74,9 @@ class ModelArguments:
         default=None,
         metadata={"help": "Auth token to log in with Hugging Face Hub."}
     )
-    upcast_layernorm: Optional[bool] = field(
-        default=False,
-        metadata={"help": "Whether to upcast the layernorm weights in fp32."}
+    export_dir: Optional[str] = field(
+        default=None,
+        metadata={"help": "Path to the directory to save the exported model."}
     )
 
     def __post_init__(self):