【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记

ChatGLM-6B是清华大学知识工程和数据挖掘小组发布的一个类似ChatGPT的开源对话机器人,由于该模型是经过约1T标识符的中英文训练,且大部分都是中文,因此十分适合国内使用。

预期环境

本机电脑备注: Win10专业版+ 32G内存+256固态系统盘+1T机械硬盘+4G英伟达显卡
python版本:3.10.7

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第1张图片

下载代码GLM-6B

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第2张图片

依赖Python库及版本

文件记录了ChatGLM-6B依赖的Python库及版本,如下:
【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第3张图片

命令执行

pip install -r requirements.txt

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第4张图片

Lucky@Lucky MINGW64 /e/ikbp/ChatGLM-6B (main)
$ pip install -r requirements.txt
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[notice] A new release of pip available: 22.2.2 -> 23.1.2
[notice] To update, run: python.exe -m pip install --upgrade pip

预训练文件

下载INT4量化后的预训练结果文件 ,INT4量化的预训练文件下载地址:https://huggingface.co/THUDM/chatglm-6b-int4/tree/main。需要注意的是在GitHub上官方提供了模型在清华云上的下载地址,但是那个只包含预训练结果文件,即bin文件,但实际上ChatGLM-6B的运行需要模型的配置文件,即config.json等,如下图所示:
【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第5张图片

从HuggingFace上下载所有文件到本地。上述文件全部下载之后保存到本地的一个目录下即可,我保存在:E:\ikbp\chatglm-6b-int4
【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第6张图片

如果以上代码输出的是True,那么恭喜你,你安装的是cuda版本的torch(注意,有显卡也需要大家下载cuda和cudann安装成功才可以,这部分大家可以去网上找教程)。

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第7张图片
##Win+GPU部署方案

Win+GPU方案的必备条件

部署GPU版本的ChatGLM-6B需要安装cuda版本的torch,大家需要检测自己的torch是否正确,可以通过如下命令检查(下面是python代码):

pip install torch

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第8张图片

下载cuda和cudann安装

win10安装CUDA和cuDNN详解

下载和安装CUDA

  • 下载CUDA
    下载地址:https://developer.nvidia.com/cuda-downloads
    【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第9张图片
    直接终端输入命令nvcc --version,即可显示

下载和安装cuDNN

  • 下载cuDNN
    下载地址:https://developer.nvidia.com/rdp/cudnn-download

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第10张图片
选择合适的版本下载就行啦,注意:一定要选择和你安装的CUDA匹配的版本。
【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第11张图片

【ChatGLM】ChatGLM-6B模型Win+4GB显卡本地部署笔记_第12张图片

附件

https://online2023.worldaic.com.cn/exhibition
ChatGLM-6B模型——Windows+6GB显卡本地部署
ChatGLM-6B/blob/main/requirements.txt
THUDM chatglm-6b-int4
win10安装CUDA和cuDNN详解
CUDA Toolkit 12.2 Downloads
cuDNN Archive

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