diff --git a/src/lmflow/args.py b/src/lmflow/args.py
index dbe6fbb3..085d090b 100644
--- a/src/lmflow/args.py
+++ b/src/lmflow/args.py
@@ -238,8 +238,8 @@ class ModelArguments:
         metadata={
             "help": "Merging ratio between the fine-tuned model and the original. This is controlled by a parameter called alpha in the paper."},
     )
-    lora_target_modules: List[str] = field(
-        default=None, metadata={"help": "Pretrained config name or path if not the same as model_name",}
+    lora_target_modules: str = field(
+        default=None, metadata={"help": "Model modules to apply LoRA to. Use comma to separate multiple modules."}
     )
     lora_dropout: float = field(
         default=0.1,
@@ -364,6 +364,9 @@ def __post_init__(self):
             if not is_flash_attn_available():
                 self.use_flash_attention = False
                 logger.warning("Flash attention is not available in the current environment. Disabling flash attention.")
+                
+        if self.lora_target_modules is not None:
+            self.lora_target_modules: List[str] = split_args(self.lora_target_modules)
 
 
 @dataclass
@@ -1464,3 +1467,7 @@ class AutoArguments:
 
     def get_pipeline_args_class(pipeline_name: str):
         return PIPELINE_ARGUMENT_MAPPING[pipeline_name]
+
+
+def split_args(args):
+    return [elem.strip() for elem in args.split(",")] if isinstance(args, str) else args
\ No newline at end of file
diff --git a/src/lmflow/utils/constants.py b/src/lmflow/utils/constants.py
index f0278985..04ad5696 100644
--- a/src/lmflow/utils/constants.py
+++ b/src/lmflow/utils/constants.py
@@ -386,12 +386,17 @@
 DEFAULT_IM_END_TOKEN = "<im_end>"
 
 # Lora
-# NOTE: Be careful, when passing lora_target_modules through arg parser, the 
-# value should be like'--lora_target_modules q_proj, v_proj \', while specifying
-# here, it should be in list format.
+# NOTE: This work as a mapping for those models that `peft` library doesn't support yet, and will be 
+# overwritten by peft.utils.constants.TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING
+# if the model is supported (see hf_model_mixin.py).
+# NOTE: When passing lora_target_modules through arg parser, the 
+# value should be a string. Using commas to separate the module names, e.g.
+# "--lora_target_modules 'q_proj, v_proj'". 
+# However, when specifying here, they should be lists.
 LMFLOW_LORA_TARGET_MODULES_MAPPING = {
     'qwen2': ["q_proj", "v_proj"],
     'internlm2': ["wqkv"],
+    'hymba': ["x_proj.0", "in_proj", "out_proj", "dt_proj.0"]
 }
 
 # vllm inference