md/install-nvidia-smi.md

https://release-assets.githubusercontent.com/github-production-release-asset/599547518/86e5d099-4113-4864-885d-477eef5b96d1?sp=r&sv=2018-11-09&sr=b&spr=https&se=2025-10-14T06%3A11%3A35Z&rscd=attachment%3B+filename%3Dvllm-0.11.0%2Bcu129-cp38-abi3-manylinux1_x86_64.whl&rsct=application%2Foctet-stream&skoid=96c2d410-5711-43a1-aedd-ab1947aa7ab0&sktid=398a6654-997b-47e9-b12b-9515b896b4de&skt=2025-10-14T05%3A11%3A27Z&ske=2025-10-14T06%3A11%3A35Z&sks=b&skv=2018-11-09&sig=K5fsBNu8iTnpIOxx74%2FiRdKUvXFKwBgbPvag31fNvK0%3D&jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmVsZWFzZS1hc3NldHMuZ2l0aHVidXNlcmNvbnRlbnQuY29tIiwia2V5Ijoia2V5MSIsImV4cCI6MTc2MDQyMzc3MCwibmJmIjoxNzYwNDIwMTcwLCJwYXRoIjoicmVsZWFzZWFzc2V0cHJvZHVjdGlvbi5ibG9iLmNvcmUud2luZG93cy5uZXQifQ.87opohoWBGdb2N7dd6xVrQ8y4GrmweyLUtk1krr3fUg&response-content-disposition=attachment%3B%20filename%3Dvllm-0.11.0%2Bcu129-cp38-abi3-manylinux1_x86_64.whl&response-content-type=application%2Foctet-stream

RTX 4090 笔电操作记录

# 因清华大学开源镜像站 HTTP/403 换了中科大的镜像站，配置信息存放在这里
cat /etc/apt/sources.list
# 安装显卡驱动和CUDA
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-8
sudo apt-get install -y cuda-drivers
nvidia-smi
apt install nvidia-cuda-toolkit
nvcc -V
# 用 conda 创建了一个 python=3.12 的环境
conda create -n vllm-py12 python=3.12 -y
# 在该目录存放关于 vllm 和LLM相关的内容
cd /home/ss/vllm-py12
conda activate vllm-py12
export https_proxy=http://10.159.236.165:7890 http_proxy=http://10.159.236.165:7890 all_proxy=socks5://10.159.236.165:7891
pip install vllm --extra-index-url https://download.pytorch.org/whl/cu128