Update README.md

README.md

@@ -47,18 +47,18 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-5.7bmqa-base", trust_remote_code=True)
 model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-5.7bmqa-base", trust_remote_code=True).cuda()
-input_text = """<fim_prefix>def quick_sort(arr):
+input_text = """<｜fim▁begin｜>def quick_sort(arr):
     if len(arr) <= 1:
         return arr
     pivot = arr[0]
     left = []
     right = []
-<fim_middle>
+<｜fim▁hole｜>
         if arr[i] < pivot:
             left.append(arr[i])
         else:
             right.append(arr[i])
-    return quick_sort(left) + [pivot] + quick_sort(right)<fim_suffix>"""
+    return quick_sort(left) + [pivot] + quick_sort(right)<｜fim▁end｜>"""
 inputs = tokenizer(input_text, return_tensors="pt").cuda()
 outputs = model.generate(**inputs, max_length=128)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True)[len(input_text):])