adamtwiss/incipit-data
Incipit self-play training data Self-play games played by Incipit, a chess engine with NNUE evaluation, and used to train its networks. About 13.9 billion scored positions from about 123 million games, in viriformat. Every game was played by Incipit itself. The first generation was bootstrapped from a hand-crafted material-and-mobility evaluation (no other engine's networks, evaluations or data were used). Each later generation was played by the best network trained on the… See the full description on the dataset page: https://huggingface.co/datasets/adamtwiss/incipit-data.
| Author / organization | adamtwiss |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 354 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 1 October 2026 |
| Last updated at source | 16 October 2026 |
Recent changes
- 16 Oct 2026 Description: Incipit self-play training data Self-play games played by Incipit, a chess engine with NNUE evaluation, and used to train its networks. About 7.1 billion scored positions from about 66 million games, in viriformat. Every game was played by → Incipit self-play training data Self-play games played by Incipit, a chess engine with NNUE evaluation, and used to train its networks. About 13.9 billion scored positions from about 123 million games, in viriformat. Every game was played b
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