# Devtools Installation **Repository Path**: learnllms/devtools-installation ## Basic Information - **Project Name**: Devtools Installation - **Description**: 开发环境软件安装与配置 - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-02-22 - **Last Updated**: 2025-09-17 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ## Miniforge3 (Anaconda 社区版,包括了更多的开源软件) 下载地址:https://mirror.nju.edu.cn/github-release/conda-forge/miniforge/LatestRelease/ ``` $ sudo bash ./Miniforge3-24.11.3-0-Linux-x86_64.sh` ``` 为了方便多个用户使用同一份程序拷贝,建议安装路径设为 /opt/miniforge3 每个用户在登录自己账号后,执行以下命令 ``` source /opt/miniforge3/bin/activate conda init ``` 之后,需重新登录该账号。建议先创建虚拟环境,然后激活后再使用 ``` conda create -n python conda activate ``` ## CUDA 驱动 应该已经随机安装好,但是如果出现 Command not found 的问题, 解决办法: ``` export PATH=/usr/local/cuda/bin:$PATH ``` 需要将上述语句增加到(.bashrc 或者.profile)的文件末尾,重新登录,或者执行 ``` source .bashrc or source .profile ``` ## Pytorch 安装 Pytorch 前,需先检查当前 CUDA 版本 ``` $nvcc --version ``` ``` nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2024 NVIDIA Corporation Built on Fri_Jun_14_16:34:21_PDT_2024 Cuda compilation tools, release 12.6, V12.6.20 Build cuda_12.6.r12.6/compiler.34431801_0 ``` 如果当前版本是 CUDA12.6,执行安装命令 ``` pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126 ``` ## Git ``` sudo apt install git ``` ## Docker 安装参考:https://www.digitalocean.com/community/tutorials/how-to-install-and-use-docker-on-ubuntu-22-04 ```bash vim /etc/docker/daemon.json ``` ```json { "registry-mirrors": [ "https://docker.m.daocloud.io", "https://dockerproxy.com", "https://hub.uuuadc.top", "https://docker.anyhub.us.kg", "https://dockerhub.icu", "https://hub-mirror.c.163.com" ], "runtimes": { "nvidia": { "args": [], "path": "nvidia-container-runtime" } }, "data-root": "/data2" } ``` ## MongoDB Atlas https://cloud.mongodb.com/