Add llm_model_dict to choose llm and add chatglm-6b-int4 as an option

chatglm_llm.py

@@ -17,7 +17,6 @@ def torch_gc():
 
 
 class ChatGLM(LLM):
-    model_name: str
     max_token: int = 10000
     temperature: float = 0.1
     top_p = 0.9
@@ -28,20 +27,6 @@ class ChatGLM(LLM):
     def __init__(self):
         super().__init__()
 
-    def load_model(self,
-                   model_name_or_path: str = "THUDM/chatglm-6b"):
-        self.tokenizer = AutoTokenizer.from_pretrained(
-            model_name_or_path,
-            trust_remote_code=True
-        )
-        self.model = (
-            AutoModel.from_pretrained(
-                model_name_or_path,
-                trust_remote_code=True)
-            .half()
-            .cuda()
-        )
-
     @property
     def _llm_type(self) -> str:
         return "ChatGLM"
@@ -62,3 +47,17 @@ class ChatGLM(LLM):
             response = enforce_stop_tokens(response, stop)
         self.history = updated_history
         return response
+
+    def load_model(self,
+                   model_name_or_path: str = "THUDM/chatglm-6b"):
+        self.tokenizer = AutoTokenizer.from_pretrained(
+            model_name_or_path,
+            trust_remote_code=True
+        )
+        self.model = (
+            AutoModel.from_pretrained(
+                model_name_or_path,
+                trust_remote_code=True)
+            .half()
+            .cuda()
+        )