| # Contributing GPU scaling results | |
| Thank you for contributing compute. The most valuable contribution is a reproducible run, including a negative result. | |
| 1. Fork the Hugging Face repository and record the commit hash used for training. | |
| 2. Install with `pip install -e '.[benchmark]'` and run `pytest -q`. | |
| 3. Do not change a named tier config for an official comparison. New configs belong under `configs/community/` with a descriptive name. | |
| 4. Run at least seeds 7, 17, and 27 when compute permits. Use AMP consistently and report whether it was enabled. | |
| 5. Submit generated JSON result files and a short note with GPU count/model, VRAM, CUDA/driver, any OOMs, and code changes. | |
| 6. For new baselines, match data split, augmentation policy, epochs, and evaluation metrics. Report parameter count, throughput, peak memory, wall time, accuracy and NLL. | |
| 7. Do not replace or cherry-pick only favorable seeds. Report all attempted runs. | |
| Suggested PR title: `results: CIFAR-10 base on 4x H100, seeds 7/17/27`. | |