tiny fix

src/utils/common.py

@@ -101,10 +101,10 @@ def _init_adapter(
         logger.info("Fine-tuning method: LoRA")
         lastest_checkpoint = None
 
+        if model_args.checkpoint_dir is not None:
             assert os.path.exists(os.path.join(model_args.checkpoint_dir[0], CONFIG_NAME)), \
                 "The given checkpoint is not a LoRA checkpoint, please specify `--finetuning_type full/freeze` instead."
 
-        if model_args.checkpoint_dir is not None:
             if (is_trainable and model_args.resume_lora_training) or (not is_mergeable): # continually train on the lora weights
                 checkpoints_to_merge, lastest_checkpoint = model_args.checkpoint_dir[:-1], model_args.checkpoint_dir[-1]
             else: