diff --git a/Evaluation/PAL-Math/run.py b/Evaluation/PAL-Math/run.py
index a3bc4de..5194046 100644
--- a/Evaluation/PAL-Math/run.py
+++ b/Evaluation/PAL-Math/run.py
@@ -29,9 +29,7 @@ def load_data(args):
     :param args: Arguments.
     :return: A list of examples.
     """
-    if args.chat_model:
-        prompt = "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n"
-    elif args.data_name != "math":
+    if args.data_name != "math":
         prompt = open("prompts/gsm8k.md").read()
     else:
         prompt = open("prompts/math.md").read()
@@ -48,10 +46,7 @@ def load_data(args):
         idx = example['idx']
         example['question'] = parse_question(example, args.data_name)
         gt_cot, gt_ans = parse_ground_truth(example, args.data_name)
-        if args.chat_model:
-            example["input"] = f"{prompt}\n### Instruction:\n{example['question']}\nWrite a python function called 'def solution():' without any arguments to return the answer without any words. In the function, write the solution steps at first and then write the code.\n### Response:\n"
-        else:
-            example["input"] = f"{prompt}\n\nQuestion: {example['question']}\n"
+        example["input"] = f"{prompt}\n\nQuestion: {example['question']}\n"
         example = {'idx': idx, 'question': example['question'], 'gt_cot': gt_cot, 'gt': gt_ans, 'prompt': example["input"]}
         samples.append(example)  
 
@@ -91,7 +86,7 @@ def inference(args):
         print("=" * 50)
 
     stop_ids = []
-    stop_words = ["Question","----------------","<|EOT|>"]
+    stop_words = ["Question","----------------"]
     for x in stop_words:
         ids = tokenizer.encode(x)
         if tokenizer.decode(ids[-1:]) == x:
@@ -185,7 +180,6 @@ if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument("--data_name", default="math", type=str)
     parser.add_argument("--model_name_or_path", default="deepseek/deepseek-coder-1b-python", type=str)
-    parser.add_argument("--chat_model", action="store_true")
     parser.add_argument("--batch_size", default=16, type=int)
     parser.add_argument("--max_context_length", default=2048, type=int)
     parser.add_argument("--max_output_length", default=512, type=int)