TinyRouter is a routing accuracy competition on the Gittensor network (Bittensor Subnet 74).
Only PRs that demonstrably improve routing accuracy are merged for TAO rewards. General improvements (docs, fixes, refactors) are welcome but earn no TAO.
Compete to train the best coordinator. If your head beats the current best accuracy on the hidden benchmark, your PR gets merged and you earn TAO.
→ Read SUBMITTING.md for the full guide.
Quick start:
# 1. Train
python -m trinity.train --benchmark math500 --run-name my-run
# 2. Pack
python scripts/pack_submission.py --run-dir experiments/math500/my-run \
--miner-name your-name --benchmark math500
# 3. Submit as PR
# See SUBMITTING.md for PR formatBug fixes, documentation, test coverage, and code quality improvements are always welcome. These PRs follow normal open-source workflow.
git clone https://github.com/James-CUDA/Gittensor-TinyRouter.git
cd Gittensor-TinyRouter
pip install -e ".[dev]"
source ~/.config/trinity/secrets.env # exports OPENROUTER_API_KEYSee AGENTS.md for the full compute environment description.
- Match the existing code. Look at adjacent files before writing.
- Line length: 100 characters
- Docstrings: Google style. Every public function gets one.
- Type annotations: required for all public functions.
- Lazy imports: torch, transformers, datasets are imported inside functions (the dev box has no GPU).
pytest tests/
ruff check src/
mypy src/Pull requests also run the offline GitHub Actions lane described in docs/CI.md.
Every non-obvious decision, mistake, or finding goes in docs/JOURNAL.md. Read it before starting significant work.
| Rule | Detail |
|---|---|
| Rate limit | 1 submission per day (enforced in code) |
| Original work | Every submission is checked against all previous heads via cosine similarity. Copies are rejected |
| Hidden benchmark | Encrypted, never revealed — don't ask for it |
| Score feedback | Winners get full results. Losers get only composite score + delta — no component breakdown |
| Receipt | Must show cost ≥ $15 and a plausible CMA-ES fitness curve. Fabricated receipts fail validation |
| Evaluation | 70% cached single-turn + 15% live multi-turn + 10% efficiency + 5% novelty (computed vs current king) |
See SUBMITTING.md for full competition rules.