model-serving
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.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install ancoleman-ai-design-components-model-serving
Repository
Skill path: skills/model-serving
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.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, DevOps, Data / AI.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: ancoleman.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install model-serving into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/ancoleman/ai-design-components before adding model-serving to shared team environments
- Use model-serving for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.