model-serving
byancoleman· 58 skills
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
How to install model-serving?
ancoleman/ai-design-components/model-serving
$npx -y skills add ancoleman/ai-design-components --skill model-servingInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/ancoleman/ai-design-components" --skill "ancoleman/ai-design-components/model-serving"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/ancoleman/ai-design-components" that are relevant to the current task. Run `npx skills add "https://github.com/ancoleman/ai-design-components"` and select the relevant skills, then follow their instructions.
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