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Langchain-Chatchat
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update chatglm_llm.py

This commit is contained in:
imClumsyPanda 2023-04-22 12:20:08 +08:00
parent 2224decef3
commit 54c983f4bc
1 changed files with 9 additions and 8 deletions
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17
models/chatglm_llm.py
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@ -72,29 +72,29 @@ class ChatGLM(LLM):
response, _ = self.model.chat( response, _ = self.model.chat(
self.tokenizer, self.tokenizer,
prompt, prompt,
history=self.history[-self.history_len:] if self.history_len>0 else [], history=self.history[-self.history_len:] if self.history_len > 0 else [],
max_length=self.max_token, max_length=self.max_token,
temperature=self.temperature, temperature=self.temperature,
) )
torch_gc() torch_gc()
if stop is not None: if stop is not None:
response = enforce_stop_tokens(response, stop) response = enforce_stop_tokens(response, stop)
self.history = self.history+[[None, response]] self.history = self.history + [[None, response]]
return response return response
def chat(self, def chat(self,
prompt: str) -> str: prompt: str) -> str:
response, _ = self.model.chat( response, _ = self.model.chat(
self.tokenizer, self.tokenizer,
prompt, prompt,
history=[],#self.history[-self.history_len:] if self.history_len>0 else history=self.history[-self.history_len:] if self.history_len > 0 else [],
max_length=self.max_token, max_length=self.max_token,
temperature=self.temperature, temperature=self.temperature,
) )
torch_gc() torch_gc()
self.history = self.history+[[None, response]] self.history = self.history + [[None, response]]
return response return response
def load_model(self, def load_model(self,
model_name_or_path: str = "THUDM/chatglm-6b", model_name_or_path: str = "THUDM/chatglm-6b",
llm_device=LLM_DEVICE, llm_device=LLM_DEVICE,
@ -126,7 +126,7 @@ class ChatGLM(LLM):
AutoModel.from_pretrained( AutoModel.from_pretrained(
model_name_or_path, model_name_or_path,
config=model_config, config=model_config,
trust_remote_code=True, trust_remote_code=True,
**kwargs) **kwargs)
.half() .half()
.cuda() .cuda()
@ -159,7 +159,8 @@ class ChatGLM(LLM):
new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v
self.model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict) self.model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
self.model.transformer.prefix_encoder.float() self.model.transformer.prefix_encoder.float()
except Exception: except Exception as e:
print(e)
print("加载PrefixEncoder模型参数失败") print("加载PrefixEncoder模型参数失败")
self.model = self.model.eval() self.model = self.model.eval()