Serve a model on one node

Run from the repository root on the allocated serving node. Read the vLLM quickstart for the exact installation and foreground launch commands. This skill does not allocate a GPU or authorize a workload.

Preconditions

• Confirm permission for the node, one isolated GPU, package installation, server startup and the validator's inference request. Record the allocation and the process you own. Never use a login shell outside that allocation or override scheduler device isolation.
• Confirm model license, immutable revision, complete file list, reader identity, cache mount and served alias. Use manage-model-cache for missing files; do not make consumers download them.
• Require Python 3.12 and a fresh private serving environment using examples/vllm/requirements.txt. Check wheel/driver compatibility against the quickstart; do not change drivers or the cache writer's environment.
• Keep the whole Hub cache read-only, including blobs. Keep authentication, HF_HOME, Xet and framework caches private. Pause snapshot writes during use.

Procedure and success gate

1. Follow quickstart steps 1–2. Require cache validator exit 0 and ok: true as the actual reader before startup. Config alone is not a complete model; name every required weight shard and tokenizer file.
2. Use quickstart step 3 unchanged for the public example: local snapshot and tokenizer, offline loading, one GPU, foreground process, loopback only. Never enable remote model code. HF_HUB_OFFLINE=1 is not a firewall and belongs only on the loading process, not globally on clients.
3. Wait for startup; use another shell in the same allocation and namespace to validate. This submits inference, not just a read-only health check:

python3 scripts/validation/validate_vllm.py --json \
  --base-url http://127.0.0.1:8000 --model deepops-gpt2 \
  --cache-dir /shared/hf-cache/hub \
  --repo-id openai-community/gpt2 \
  --revision 607a30d783dfa663caf39e06633721c8d4cfcd7e \
  --require-file config.json --require-file tokenizer.json --require-file model.safetensors

4. Require exit 0 and ok: true. Schema version 1 checks cache, health, advertised model and bounded completion in order. Exit 1 fails validation; exit 2 is a command syntax error without guaranteed JSON. A false check can mean skipped; inspect the first error stage. Preserve the invocation, package versions and private startup log. Success does not prove loaded revision, GPU use, quality or throughput; an alias alone is not revision attestation.
5. Stop only your own foreground server with Ctrl-C. Confirm exit before releasing the allocation. Do not kill another listener or prune the shared cache.

Stop and recovery

Offline fixtures test the validator, not real cache reuse, GPU inference or agent decision-making. Those require separate verification.