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serving-llms-on-instinct

Serves AI models on AMD Instinct GPU hardware using vLLM. Use this skill whenever the user wants to run, serve, deploy, start, host, or launch a language model on an AMD GPU, AMD Instinct, MI300X, MI325X, MI350X, or MI355X. Also use when the user mentions vLLM on ROCm, vLLM on AMD, serving on HBM, or asks how to get a model running on AMD data center hardware. Use when the user asks "run Qwen3", "serve DeepSeek", "start a vLLM endpoint", "get a model running on my AMD machine", or any similar phrasing. Handles the full flow: GPU detection, environment validation, vLLM configuration, launch, and health verification. Do not use for NVIDIA GPUs, consumer AMD GPUs (RX series, Radeon), Ryzen AI, NPU, MI250X, or MI100.

skills/serving-llms-on-instinct/SKILL.md

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Last checked
Nov 6, 2026

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481
Repository last updated
Nov 6, 2026
License
MIT

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# Serving LLMs on AMD Instinct

Get a vLLM endpoint running on AMD Instinct GPU hardware.

## Prerequisites

- ROCm driver and `amd-smi` installed on the GPU host
- Docker running and accessible (check with `docker ps`)
- `/dev/kfd` and `/dev/dri` present on the GPU host
- HuggingFace token in `HF_TOKEN` env var (required for gated models; not
  required for Qwen3 or Gemma). For gated models (Llama 3.2, Gemma, etc.),
  the HF token must belong to an account that has accepted the model's license
  at `huggingface.co/<model_id>`. A valid token without license acceptance will
  fail with an opaque "Engine core initialization failed" error.