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cli_demo.py 3.00 KB
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张涵 提交于 2023-07-04 15:30 . 修改部分文件
import os
import platform
import signal
import torch
from transformers import AutoConfig, AutoModel, AutoTokenizer
import readline
modelPath = "chatglm-6b"
# 可以正常输出,但是回答问题不对应
# checkpointPath = "ptuning/output/adgen-chatglm-6b-pt-128-2e-2-1/checkpoint-1000"
# 输出中含有<UNK>
# checkpointPath = "ptuning/output/adgen-chatglm-6b-pt-128-2e-2-1/checkpoint-2000"
# 输出中含有<UNK>
# checkpointPath = "ptuning/output/adgen-chatglm-6b-pt-128-2e-2-1/checkpoint-3000"
# 重复回答一个答案
# checkpointPath = "ptuning/output/adgen-chatglm-6b-pt-128-2e-1-weitiao1/checkpoint-1000"
checkpointPath = "ptuning/output/adgen-chatglm-6b-pt-128-2e-2-微调3/checkpoint-3000"
preSeqLen = 128
# Load model and tokenizer of ChatGLM-6B
config = AutoConfig.from_pretrained(modelPath, trust_remote_code=True, pre_seq_len=preSeqLen)
tokenizer = AutoTokenizer.from_pretrained(modelPath, trust_remote_code=True)
model = AutoModel.from_pretrained(modelPath, config=config, trust_remote_code=True)
# Load PrefixEncoder
prefix_state_dict = torch.load(os.path.join(checkpointPath, "pytorch_model.bin"))
new_prefix_state_dict = {}
for k, v in prefix_state_dict.items():
new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v
model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
print(f"Quantized to 4 bit")
model = model.quantize(4)
model = model.half().cuda()
model.transformer.prefix_encoder.float()
model = model.eval()
os_name = platform.system()
clear_command = 'cls' if os_name == 'Windows' else 'clear'
stop_stream = False
def build_prompt(history):
prompt = "欢迎使用 ChatGLM-6B 模型,输入内容即可进行对话,clear 清空对话历史,stop 终止程序"
for query, response in history:
prompt += f"\n\n用户:{query}"
prompt += f"\n\nChatGLM-6B:{response}"
return prompt
def signal_handler(signal, frame):
global stop_stream
stop_stream = True
def main():
history = []
global stop_stream
print("欢迎使用 ChatGLM-6B 模型,输入内容即可进行对话,clear 清空对话历史,stop 终止程序")
while True:
query = input("\n用户:")
if query.strip() == "stop":
break
if query.strip() == "clear":
history = []
os.system(clear_command)
print("欢迎使用 ChatGLM-6B 模型,输入内容即可进行对话,clear 清空对话历史,stop 终止程序")
continue
count = 0
for response, history in model.stream_chat(tokenizer, query, history=history):
if stop_stream:
stop_stream = False
break
else:
count += 1
if count % 8 == 0:
os.system(clear_command)
print(build_prompt(history), flush=True)
signal.signal(signal.SIGINT, signal_handler)
os.system(clear_command)
print(build_prompt(history), flush=True)
if __name__ == "__main__":
main()
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