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cli_demo.py
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cli_demo.py
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import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
import torch
import platform
import subprocess
from colorama import Fore, Style
from tempfile import NamedTemporaryFile
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation.utils import GenerationConfig
def init_model():
print("init model ...")
model = AutoModelForCausalLM.from_pretrained(
"OrionStarAI/OrionStar-Yi-34B-Chat",
torch_dtype=torch.float16,
device_map="auto",
trust_remote_code=True,
use_safetensors=False
)
model.generation_config = GenerationConfig.from_pretrained(
"OrionStarAI/OrionStar-Yi-34B-Chat",
)
tokenizer = AutoTokenizer.from_pretrained(
"OrionStarAI/OrionStar-Yi-34B-Chat",
use_fast=False,
trust_remote_code=True
)
return model, tokenizer
def clear_screen():
if platform.system() == "Windows":
os.system("cls")
else:
os.system("clear")
print(
Fore.YELLOW + Style.BRIGHT + "欢迎使用OrionStar-Yi-34B-Chat,输入进行对话,vim 多行输入,clear 清空历史,CTRL+C 中断生成,stream 开关流式生成,exit 结束。")
return []
def vim_input():
with NamedTemporaryFile() as tempfile:
tempfile.close()
subprocess.call(['vim', '+star', tempfile.name])
text = open(tempfile.name).read()
return text
def main(stream=True):
model, tokenizer = init_model()
messages = clear_screen()
while True:
prompt = input(Fore.GREEN + Style.BRIGHT + "\n用户:" + Style.NORMAL)
if prompt.strip() == "exit":
break
if prompt.strip() == "clear":
messages = clear_screen()
continue
if prompt.strip() == 'vim':
prompt = vim_input()
print(prompt)
print(Fore.CYAN + Style.BRIGHT + "\nOrionStar-Yi-34B:" + Style.NORMAL, end='')
if prompt.strip() == "stream":
stream = not stream
print(Fore.YELLOW + "({}流式生成)\n".format("开启" if stream else "关闭"), end='')
continue
messages.append({"role": "user", "content": prompt})
if stream:
position = 0
try:
for response in model.chat(tokenizer, messages, streaming=True):
print(response[position:], end='', flush=True)
position = len(response)
if torch.backends.mps.is_available():
torch.mps.empty_cache()
except KeyboardInterrupt:
pass
print()
else:
response = model.chat(tokenizer, messages)
print(response)
if torch.backends.mps.is_available():
torch.mps.empty_cache()
messages.append({"role": "assistant", "content": response})
print(Style.RESET_ALL)
if __name__ == "__main__":
main()