What is vllm-deploy-docker?
Deploy vLLM using Docker (pre-built images or build-from-source) with NVIDIA GPU support and run the OpenAI-compatible server. Source: vllm-project/vllm-skills.
Deploy vLLM using Docker (pre-built images or build-from-source) with NVIDIA GPU support and run the OpenAI-compatible server.
Quickly install vllm-deploy-docker AI skill to your development environment via command line
Source: vllm-project/vllm-skills.
A Claude skill describing how to deploy vLLM with Docker using the official pre-built images or building the image from source supporting NVIDIA GPUs with CUDA. Instructions include NVIDIA CUDA support, example docker run and a minimal docker-compose snippet, recommended flags, and troubleshooting notes. For AMD, Intel, or other accelerators, please refer to the vLLM documentation for alternative deployment methods.
Run a vLLM OpenAI-compatible server with GPU access, mounting the HF cache and forwarding port 8000:
Note: vLLM and this skill recommend using the latest Docker image (vllm/vllm-openai:latest). For legacy version images, you may refer to the Docker Hub image tags.
Deploy vLLM using Docker (pre-built images or build-from-source) with NVIDIA GPU support and run the OpenAI-compatible server. Source: vllm-project/vllm-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/vllm-project/vllm-skills --skill vllm-deploy-dockerDeploy vLLM using Docker (pre-built images or build-from-source) with NVIDIA GPU support and run the OpenAI-compatible server. Source: vllm-project/vllm-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/vllm-project/vllm-skills --skill vllm-deploy-docker Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/vllm-project/vllm-skills