Files
club-3090/docs/GETTING_STARTED.md
noonghunna 7e9f5cb930 serve: neutral primary model name (qwen3.6-27b / gemma-4-31b), keep -autoround alias
The shared served-model-name `qwen3.6-27b-autoround` (from #490) mislabels the
non-autoround 27b scenes (fp8 dual-max, lmcache): /v1/models advertises
"autoround" while `root` points at qwen3.6-27b-fp8. Same class on gemma-4-31b —
after the v0.24.0 consolidation the default is cyankiwi qat-AWQ-INT4 (bf16 KV),
yet the LiteLLM route still targeted `gemma-4-31b-autoround` (a latent #482 drift).

Fix WITHOUT breaking anything, via vLLM multi-served-name:
- Every 27b scene now serves `qwen3.6-27b <its-quant-name>`; every gemma-31b
  scene serves `gemma-4-31b <its-quant-name>`. The neutral name is PRIMARY
  (honest /v1/models id); the quant-specific name is retained as a live ALIAS.
- LiteLLM: add `qwen3.6-27b` / `gemma-4-31b` canonical public routes; keep the
  `-autoround` routes as back-compat aliases (same upstream). Repairs the gemma drift.
- Migrate our own MODEL= defaults + docs (bench/verify/quality/launch/setup, c3,
  tui-core, EXAMPLES, ...) to the neutral name. Weights slugs (`-autoround-int4`)
  untouched; CHANGELOG + results/ history left as-is.

Retiring the `-autoround` alias entirely is a deliberate later step once nothing
still asks for it.

Live-verified on-rig (single/minimal, stock v0.24.0): /v1/models lists BOTH names
(root=...-autoround-int4); chat to `qwen3.6-27b` AND `qwen3.6-27b-autoround` both
return 200; `qwen3.6-27b-fp8` correctly 404s. Full shell gate 59/59 (1 = known
worktree-fixture); c3 pytest 41 passed; served-name arg-order + YAML validated.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EfF565T9eSLaqGzidyJ1Pm
2026-07-02 11:28:31 +00:00

2.0 KiB

Getting started — zero to curl in 5 minutes

The fastest path from git clone to serving your first response. No decisions, no menus — just commands.

New to local AI and the terms below feel like jargon? Read LOCAL_AI_PRIMER.md first — how hardware, engines, model sizes, and quants fit together in plain English.

# 1. Clone
git clone https://github.com/noonghunna/club-3090.git
cd club-3090

# 2. Download the model (Qwen3.6-27B, ~18 GB)
bash scripts/setup.sh qwen3.6-27b

# 3. Boot the default config for this model on your hardware
#    (auto-picks: single-card → ik-llama/iq4ks-mtp; dual → vllm/dual)
bash scripts/launch.sh --variant qwen3.6-27b/default

# 4. Test it
curl -sf http://localhost:8020/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen3.6-27b","messages":[{"role":"user","content":"Capital of France?"}],"max_tokens":200}'

If you see Paris in the response, you're up and running.

After the boot finishes, launch.sh asks "Make <slug> your default for qwen3.6-27b? [y/N]". Say y and a bare bash scripts/launch.sh next time goes straight to that exact config — no flags, one keypress to launch. (Change or clear it anytime: bash scripts/switch.sh --set-default <slug> / --clear-default qwen3.6-27b.)


Next steps

You want Go here
Pick a config by workload (long context, vision, dual-card, etc.) docs/SINGLE_CARD.md or docs/DUAL_CARD.md
Understand the jargon (TPS, KV, MTP, TP) docs/GLOSSARY.md
Client code snippets (Python, curl, IDE setup) docs/EXAMPLES.md
Run the canonical benchmark bash scripts/bench.sh
Update to the latest bash scripts/update.sh
Hardware questions (power caps, NVLink, 4090/5090) docs/HARDWARE.md
File an issue or share bench numbers bash scripts/report.sh --full > my-rig.md and open an issue