LLM

LLM.py

@@ -7,25 +7,25 @@ import torch
 
 
 class ChatGLM_LLM(LLM):
-    # 基于本地 InternLM 自定义 LLM 类
+    # 锟斤拷锟节憋拷锟斤拷 InternLM 锟皆讹拷锟斤拷 LLM 锟斤拷
     tokenizer: AutoTokenizer = None
     model: AutoModelForCausalLM = None
 
     def __init__(self, model_path: str):
-        # model_path: InternLM 模型路径
-        # 从本地初始化模型
+        # model_path: InternLM 模锟斤拷路锟斤拷
+        # 锟接憋拷锟截筹拷始锟斤拷模锟斤拷
         super().__init__()
-        print("正在从本地加载模型...")
+        print("锟斤拷锟节从憋拷锟截硷拷锟斤拷模锟斤拷...")
         self.tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
         self.model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True).to(torch.bfloat16).cuda(
             device=1)
         self.model = self.model.eval()
-        print("完成本地模型的加载")
+        print("锟斤拷杀锟斤拷锟侥ｏ拷偷募锟斤拷锟�")
 
     def _call(self, prompt: str, stop: Optional[List[str]] = None,
               run_manager: Optional[CallbackManagerForLLMRun] = None,
               **kwargs: Any):
-        # 重写调用函数
+        # 锟斤拷写锟斤拷锟矫猴拷锟斤拷
         response, history = self.model.chat(self.tokenizer, prompt, history=[], do_sample=False)
         return response