Run Hugging Face Training Smoke

Run the smallest experiment that can disprove the training setup. Treat a passing smoke as permission to consider a longer run, never as model or product acceptance.

Establish the boundary

1. Record the hypothesis, maximum optimizer steps, hardware, timeout, budget, seed, and stop gates.
2. Freeze dataset splits, model revision, tokenizer revision, prompt contract, held-out manifest, and validator revision. Hash local inputs before renting compute.
3. Confirm the user has authorized paid compute and any artifact upload. Keep repositories private unless explicitly told otherwise.
4. Load credentials from the authorized environment without printing or copying them into commands, logs, manifests, or source.

Preflight locally

Run scripts/preflight_runner.py against the exact submitted runner: