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Windows 11 上从零开始基于 wsl-ubuntu 搭建 AI 学习环境及部署多种私有 ChatGPT

Windows 11 上从零开始基于 wsl-ubuntu 搭建 AI 学习环境及部署多种私有 ChatGPT

0. 背景和简介

今天(2023/6/2)刚刚换了 1 块 4TB 的硬盘,在 Windows 11 上从零开始,基于 Windows Subsystem for Linux 搭建一套 AI 学习环境。

其中包括,安装 Python、安装 Miniconda3、安装 CUDA Toolkit、安装 git lfs、配置 Hugging Face 的缓存路径、本地部署 ChatGLM-6B、本地部署 VisualGLM-6B等等内容。

1. 安装 wsl-ubuntu

  1. 安装 Ubuntu-22.04,默认会安装在 C 盘,
wsl.exe --install -d Ubuntu-22.04
  1. 导出 Ubuntu-22.04,
wsl --export Ubuntu-22.04 D:\tmp\Ubuntu-22.04.tar
  1. 删除 Ubuntu-22.04,
wsl --unregister Ubuntu-22.04
  1. 导入 Ubuntu-22.04,导入到 F:\VirtualPCs\Ubutun-22.04 目录,
wsl --import Ubuntu-22.04 F:\VirtualPCs\Ubutun-22.04 D:\tmp\Ubuntu-22.04.tar
  1. 访问 Ubuntu-22.04,
wsl
  1. 退出 Ubuntu-22.04,
exit
  1. (可选)关闭 Ubuntu-22.04,
wsl --shutdown

2. (可选)配置清华大学软件源

  1. 为了加速软件安装速度,配置清华大学软件源,
mv /etc/apt/sources.list /etc/apt/sources.list.bak
cat << EOF > /etc/apt/sources.list
# 默认注释了源码镜像以提高 apt update 速度,如有需要可自行取消注释
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-updates main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-updates main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-backports main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-backports main restricted universe multiverse

# deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-security main restricted universe multiverse
# # deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-security main restricted universe multiverse

deb http://security.ubuntu.com/ubuntu/ jammy-security main restricted universe multiverse
# deb-src http://security.ubuntu.com/ubuntu/ jammy-security main restricted universe multiverse

# 预发布软件源,不建议启用
# deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-proposed main restricted universe multiverse
# # deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-proposed main restricted universe multiverse
EOF

3. 系统更新

sudo apt update && sudo apt upgrade

4. 安装 Python

  1. 安装必要的构建工具,
sudo apt install build-essential checkinstall
sudo apt install libncursesw5-dev libssl-dev libsqlite3-dev tk-dev libgdbm-dev libc6-dev libbz2-dev
  1. 下载Python 3.10.6 源代码,
cd /tmp
wget https://www.python.org/ftp/python/3.10.6/Python-3.10.6.tar.xz
tar -xvf Python-3.10.6.tar.xz
cd Python-3.10.6/
  1. 配置和安装Python 3.10,
./configure --enable-optimizations
sudo make altinstall
altinstall

选项会安装Python 3.10到

/usr/bin/python3.10

,这样不会对系统默认的Python产生影响。

  1. (可选)配置环境变量,
echo 'export PATH="/usr/bin/python3.10:$PATH"' >> ~/.bashrc 
source ~/.bashrc
  1. 配置软链接,
ln -s /usr/local/bin/python3.10 /usr/local/bin/python3
ln -s /usr/local/bin/python3.10 /usr/local/bin/python
ln -s /usr/local/bin/pip3.10 /usr/local/bin/pip3
ln -s /usr/local/bin/pip3.10 /usr/local/bin/pip
  1. 验证Python 3.10是否安装成功,
python3 --version

--- 输出
Python 3.10.6
---
pip3 --version

--- 输出
pip 22.2.1 from /usr/local/lib/python3.10/site-packages/pip (python 3.10)
---

5. 安装 Miniconda3

  1. 下载 Conda 安装脚本,
cd /tmp
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
  1. 运行安装脚本,按提示操作,当提示是否初始化 Conda 时,输入 “yes”,
bash Miniconda3-latest-Linux-x86_64.sh

---
Please, press ENTER to continue
>>> yes

Do you accept the license terms? [yes|no]
[no] >>> yes

Miniconda3 will now be installed into this location:
/root/miniconda3

  - Press ENTER to confirm the location
  - Press CTRL-C to abort the installation
  - Or specify a different location below

[/root/miniconda3] >>> ENTER

Do you wish the installer to initialize Miniconda3
by running conda init? [yes|no]
[no] >>> yes
---
  1. 安装完成后,激活一下 Conda,
sudo su - root
  1. 更新 Conda 至最新版本,
conda update conda
  1. 配置用户登录时是否默认激活 Conda 的 base 环境,

如果想默认激活 Conda 的 base 环境,

conda config --set auto_activate_base true

如果不想默认激活 Conda 的 base 环境,

conda config --set auto_activate_base false

6. 安装 CUDA Toolkit

refer:


本文转载自: https://blog.csdn.net/engchina/article/details/131012094
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