diff --git a/src/llamafactory/hparams/model_args.py b/src/llamafactory/hparams/model_args.py
index f86291b0..8fcfcb42 100644
--- a/src/llamafactory/hparams/model_args.py
+++ b/src/llamafactory/hparams/model_args.py
@@ -69,6 +69,10 @@ class BaseModelArguments:
         default=None,
         metadata={"help": "Special tokens to be added into the tokenizer. Use commas to separate multiple tokens."},
     )
+    new_normal_tokens: Optional[str] = field(
+        default=None,
+        metadata={"help": "Normal tokens to be added into the tokenizer. Use commas to separate multiple tokens."},
+    )
     model_revision: str = field(
         default="main",
         metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
@@ -176,6 +180,9 @@ class BaseModelArguments:
         if self.adapter_name_or_path is not None:  # support merging multiple lora weights
             self.adapter_name_or_path = [path.strip() for path in self.adapter_name_or_path.split(",")]
 
+        if self.new_normal_tokens is not None:  # support multiple normal tokens
+            self.new_normal_tokens = [token.strip() for token in self.new_normal_tokens.split(",")]
+
         if self.new_special_tokens is not None:  # support multiple special tokens
             self.new_special_tokens = [token.strip() for token in self.new_special_tokens.split(",")]
 
diff --git a/src/llamafactory/model/patcher.py b/src/llamafactory/model/patcher.py
index 28014de9..52b25110 100644
--- a/src/llamafactory/model/patcher.py
+++ b/src/llamafactory/model/patcher.py
@@ -55,14 +55,24 @@ def patch_tokenizer(tokenizer: "PreTrainedTokenizer", model_args: "ModelArgument
         tokenizer.model_max_length = model_args.model_max_length  # enlarge the tokenizer max length
 
     if model_args.new_special_tokens is not None:
-        num_added_tokens = tokenizer.add_special_tokens(
+        num_added_special_tokens = tokenizer.add_special_tokens(
             dict(additional_special_tokens=model_args.new_special_tokens),
             replace_additional_special_tokens=False,
         )
-        logger.info_rank0("Add {} to special tokens.".format(",".join(model_args.new_special_tokens)))
-        if num_added_tokens > 0 and not model_args.resize_vocab:
+        logger.info_rank0("Add special tokens {} to vocab.".format(",".join(model_args.new_special_tokens)))
+        if num_added_special_tokens > 0 and not model_args.resize_vocab:
             model_args.resize_vocab = True
-            logger.warning_rank0("New tokens have been added, changed `resize_vocab` to True.")
+            logger.warning_rank0("New special tokens have been added, changed `resize_vocab` to True.")
+
+    if model_args.new_normal_tokens is not None:
+        num_added_normal_tokens = tokenizer.add_tokens(
+            new_tokens=model_args.new_normal_tokens,
+            special_tokens=False,
+        )
+        logger.info_rank0("Add normal tokens {} to vocab.".format(",".join(model_args.new_normal_tokens)))
+        if num_added_normal_tokens > 0 and not model_args.resize_vocab:
+            model_args.resize_vocab = True
+            logger.warning_rank0("New normal tokens have been added, changed `resize_vocab` to True.")
 
 
 def patch_processor(