serving-llms-vllm
"Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism."
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Installation for Agentic Skill
View all platforms →skilz install zechenzhangAGI/AI-research-SKILLs/serving-llms-vllm skilz install zechenzhangAGI/AI-research-SKILLs/serving-llms-vllm --agent opencode skilz install zechenzhangAGI/AI-research-SKILLs/serving-llms-vllm --agent codex skilz install zechenzhangAGI/AI-research-SKILLs/serving-llms-vllm --agent gemini
First time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/zechenzhangAGI/AI-research-SKILLs cp -r AI-research-SKILLs/12-inference-serving/vllm ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- zechenzhangAGI (GitHub)
- Repository
- AI-research-SKILLs
- Type
- Technical
- Meta-Domain
- data ai
- Primary Domain
- machine learning
- Market Score
- 26.2
Browse Category
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