大模型部署手记（3）通义千问+Windows GPU

1.简介

组织机构：阿里

代码仓：GitHub - QwenLM/Qwen: The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.

模型：Qwen/Qwen-7B-Chat-Int4

下载：http://huggingface.co/Qwen/Qwen-7B-Chat-Int4

modelscope下载：https://modelscope.cn/models/qwen/Qwen-7B-Chat-Int4/summary

硬件环境：暗影精灵7Plus

Windows版本：Windows 11家庭中文版 Insider Preview 22H2

内存 32G

GPU显卡：Nvidia GTX 3080 Laptop （16G）

安装阿里的通义千问大模型有两种方式，modelscope方式和transformers（huggingface）方式。

参考资料：

1.玩一玩140亿参数的阿里千问！Qwen+Win11+3060 https://zhuanlan.zhihu.com/p/659000534

2.玩一玩通义千问Qwen开源版，Win11 RTX3060本地安装记录！ https://zhuanlan.zhihu.com/p/648368704

2.代码和模型下载

下载代码仓：

git clone https://github.com/QwenLM/Qwen.git

模型下载参见第四部分执行 python Qwen-7B-Chat-Int4.py的过程。

3.安装依赖

打开Anaconda Powershell Prompt，创建conda环境：

conda create -n model310 python=3.10

conda activate model310

安装modelscope基础库

pip install modelscope

在安装modelscope的时候，系统会自动安装pytorch 2.0.1（后面会发现装的torch这个完全不对）

打开魔搭社区 http://modelscope.cn

注册一下：

打开 Qwen-7B inr4量化的主页：https://modelscope.cn/models/qwen/Qwen-7B-Chat-Int4/summary

安装量化依赖：

pip install auto-gptq optimum

安装量化包：

pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui

安装其他依赖：

pip install transformers_stream_generator

pip install tiktoken

pip install deepspeed

目前deepspeed在windows上的安装还存在问题。我们先忽略掉吧！

安装flash-attention库

git clone -b v1.0.8 https://github.com/Dao-AILab/flash-attention

cd flash-attention

pip install .

# 下方安装可选，安装可能比较缓慢。

# Below are optional. Installing them might be slow.

# pip install csrc/layer_norm

# pip install csrc/rotary

看日志应该是torch可能不是CUDA的版本。

验证下：

果然如此。

还是使用conda安装pytorch 2.0的CUDA版本吧！

conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

为了保险，还是要验证一下：

python

import torch

#pytorch的版本

torch.__version__

#是否支持CUDA

torch.cuda.is_available()

#CUDA的版本

print(torch.version.cuda)

#cuDNN的版本

print(torch.backends.cudnn.version())

#GPU内存

torch.cuda.get_device_capability(device=0)

再来：

pip install .

4.部署验证

编辑d:\Qwen\Qwen-7B-Chat-Int4.py 文件，内容如下：

from modelscope import AutoTokenizer, AutoModelForCausalLM, snapshot_download
model_dir = snapshot_download("qwen/Qwen-7B-Chat-Int4", revision = 'v1.1.3' )# Note: The default behavior now has injection attack prevention off.
tokenizer = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained(model_dir,device_map="auto",trust_remote_code=True
).eval()
response, history = model.chat(tokenizer, "你好", history=None)
print(response)
# 你好！很高兴为你提供帮助。

执行这个文件：

cd d:\Qwen

python Qwen-7B-Chat-Int4.py

pip install chardet

再来：

python Qwen-7B-Chat-Int4.py

耐心等待模型下载完毕。。。

看来模型是下载到了这个目录：C:\Users\用户名\.cache\modelscope\hub\qwen\Qwen-7B-Chat-Int4

这个下载的时候不显示速度，下载完毕之后才显示速度。。。

仔细看看还少装了什么包：

pip install cchardet

再来：

python Qwen-7B-Chat-Int4.py

看来已经能成功运行了。

将前面下载目录 C:\Users\用户名\.cache\modelscope\hub\qwen\Qwen-7B-Chat-Int4 下的所有文件复制到当前目录的 Qwen\Qwen-7B-Chat-Int4 目录:

修改cli_demo.py

修改如下代码：

DEFAULT_CKPT_PATH = './Qwen/Qwen-7B-Chat-Int4'

运行 python cli_demo.py

系统很快会弹出：

做一些交互：

不过每次都要清屏，有点不舒服。

把代码中的clear_screen都去掉：（除了收到明确的clear命令）

CTRL-C退出去重新运行：python cli_demo.py

貌似有点问题，代码好像每次都在做刷屏，然后输入一行新的话处理。

经过多次尝试，代码这样修改就可以了：

# Copyright (c) Alibaba Cloud.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree."""A simple command-line interactive chat demo."""import argparse
import os
import platform
import shutil
from copy import deepcopyfrom transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation import GenerationConfig
from transformers.trainer_utils import set_seedDEFAULT_CKPT_PATH = './Qwen/Qwen-7B-Chat-Int4'_WELCOME_MSG = '''\
Welcome to use Qwen-Chat model, type text to start chat, type :h to show command help.
(欢迎使用 Qwen-Chat 模型，输入内容即可进行对话，:h 显示命令帮助。)Note: This demo is governed by the original license of Qwen.
We strongly advise users not to knowingly generate or allow others to knowingly generate harmful content, including hate speech, violence, pornography, deception, etc.
(注：本演示受Qwen的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，包括但不限于仇恨言论、暴力、色情、欺诈相关的有害信息。)
'''
_HELP_MSG = '''\
Commands::help / :h          Show this help message              显示帮助信息:exit / :quit / :q  Exit the demo                       退出Demo:clear / :cl        Clear screen                        清屏:clear-his / :clh   Clear history                       清除对话历史:history / :his     Show history                        显示对话历史:seed               Show current random seed            显示当前随机种子:seed <N>           Set random seed to <N>              设置随机种子:conf               Show current generation config      显示生成配置:conf <key>=<value> Change generation config            修改生成配置:reset-conf         Reset generation config             重置生成配置
'''def _load_model_tokenizer(args):tokenizer = AutoTokenizer.from_pretrained(args.checkpoint_path, trust_remote_code=True, resume_download=True,)if args.cpu_only:device_map = "cpu"else:device_map = "auto"model = AutoModelForCausalLM.from_pretrained(args.checkpoint_path,device_map=device_map,trust_remote_code=True,resume_download=True,).eval()config = GenerationConfig.from_pretrained(args.checkpoint_path, trust_remote_code=True, resume_download=True,)return model, tokenizer, configdef _clear_screen():if platform.system() == "Windows":os.system("cls")else:os.system("clear")def _print_history(history):terminal_width = shutil.get_terminal_size()[0]print(f'History ({len(history)})'.center(terminal_width, '='))for index, (query, response) in enumerate(history):print(f'User[{index}]: {query}')print(f'QWen[{index}]: {response}')print('=' * terminal_width)def _get_input() -> str:while True:try:message = input('User> ').strip()except UnicodeDecodeError:print('[ERROR] Encoding error in input')continueexcept KeyboardInterrupt:exit(1)if message:return messageprint('[ERROR] Query is empty')def main():parser = argparse.ArgumentParser(description='QWen-Chat command-line interactive chat demo.')parser.add_argument("-c", "--checkpoint-path", type=str, default=DEFAULT_CKPT_PATH,help="Checkpoint name or path, default to %(default)r")parser.add_argument("-s", "--seed", type=int, default=1234, help="Random seed")parser.add_argument("--cpu-only", action="store_true", help="Run demo with CPU only")args = parser.parse_args()history, response = [], ''model, tokenizer, config = _load_model_tokenizer(args)orig_gen_config = deepcopy(model.generation_config)#_clear_screen()print(_WELCOME_MSG)seed = args.seedwhile True:query = _get_input()# Process commands.if query.startswith(':'):command_words = query[1:].strip().split()if not command_words:command = ''else:command = command_words[0]if command in ['exit', 'quit', 'q']:breakelif command in ['clear', 'cl']:_clear_screen()print(_WELCOME_MSG)continueelif command in ['clear-history', 'clh']:print(f'[INFO] All {len(history)} history cleared')history.clear()continueelif command in ['help', 'h']:print(_HELP_MSG)continueelif command in ['history', 'his']:_print_history(history)continueelif command in ['seed']:if len(command_words) == 1:print(f'[INFO] Current random seed: {seed}')continueelse:new_seed_s = command_words[1]try:new_seed = int(new_seed_s)except ValueError:print(f'[WARNING] Fail to change random seed: {new_seed_s!r} is not a valid number')else:print(f'[INFO] Random seed changed to {new_seed}')seed = new_seedcontinueelif command in ['conf']:if len(command_words) == 1:print(model.generation_config)else:for key_value_pairs_str in command_words[1:]:eq_idx = key_value_pairs_str.find('=')if eq_idx == -1:print('[WARNING] format: <key>=<value>')continueconf_key, conf_value_str = key_value_pairs_str[:eq_idx], key_value_pairs_str[eq_idx + 1:]try:conf_value = eval(conf_value_str)except Exception as e:print(e)continueelse:print(f'[INFO] Change config: model.generation_config.{conf_key} = {conf_value}')setattr(model.generation_config, conf_key, conf_value)continueelif command in ['reset-conf']:print('[INFO] Reset generation config')model.generation_config = deepcopy(orig_gen_config)print(model.generation_config)continueelse:# As normal query.pass# Run chat.set_seed(seed)try:for response in model.chat_stream(tokenizer, query, history=history, generation_config=config):pass
#                _clear_screen()
#             print(f"\nUser: {query}")print(f"\nQwen-Chat: {response}")except KeyboardInterrupt:print('[WARNING] Generation interrupted')continuehistory.append((query, response))if __name__ == "__main__":main()

请注意print的位置。

python cli_demo.py