Update README.md

README.md

@@ -14,9 +14,18 @@ model_id=Mistral-7B-Instruct-v0.4
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id,torch_dtype=torch.bfloat16,device_map="auto",)
-prompt = "[INST] <<SYS>>\nYou are a helpful, respectful and honest assistant.Help humman as much as you can.\n<</SYS>>\n\n{instruction} [/INST]"
-text = prompt.format_map({"instruction":"你好，最近干嘛呢"})
 
+chat_template="{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}"
+
+def chat_format(conversation:list):
+    system_prompt = "You are a helpful, respectful and honest assistant.Help humman as much as you can."
+    
+    id = tokenizer.apply_chat_template(conversation,chat_template=chat_template,tokenize=False)
+    
+    return id
+
+user_chat=[{"role":"user","content":"你好，最近在干嘛呢"}]
+text = chat_format(user_chat).rstrip("</s>")
 def predict(content_prompt):
     inputs = tokenizer(content_prompt,return_tensors="pt",add_special_tokens=True)
     input_ids = inputs["input_ids"].to("cuda:0")