diff --git a/scripts/convert_model.py b/scripts/convert_model.py
index b479825..9aa8d1e 100644
--- a/scripts/convert_model.py
+++ b/scripts/convert_model.py
@@ -1,5 +1,6 @@
 import os
 import sys
+import json
 
 __package__ = "scripts"
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
@@ -25,6 +26,9 @@ def convert_torch2transformers_minimind(torch_path, transformers_path, dtype=tor
     lm_model.save_pretrained(transformers_path, safe_serialization=False)
     tokenizer = AutoTokenizer.from_pretrained('../model/')
     tokenizer.save_pretrained(transformers_path)
+    # 兼容transformers-5.0的写法
+    config_path = os.path.join(transformers_path, "tokenizer_config.json")
+    json.dump({**json.load(open(config_path, 'r', encoding='utf-8')), "tokenizer_class": "PreTrainedTokenizerFast", "extra_special_tokens": {}}, open(config_path, 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
     print(f"模型已保存为 Transformers-MiniMind 格式: {transformers_path}")
 
 
@@ -52,6 +56,9 @@ def convert_torch2transformers_llama(torch_path, transformers_path, dtype=torch.
     print(f'模型参数: {model_params / 1e6} 百万 = {model_params / 1e9} B (Billion)')
     tokenizer = AutoTokenizer.from_pretrained('../model/')
     tokenizer.save_pretrained(transformers_path)
+    # 兼容transformers-5.0的写法
+    config_path = os.path.join(transformers_path, "tokenizer_config.json")
+    json.dump({**json.load(open(config_path, 'r', encoding='utf-8')), "tokenizer_class": "PreTrainedTokenizerFast", "extra_special_tokens": {}}, open(config_path, 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
     print(f"模型已保存为 Transformers-Llama 格式: {transformers_path}")