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| title: ChessTransformer | |
| emoji: ♟️ | |
| colorFrom: indigo | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 5.49.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Play a chess transformer trained only on human games | |
| # ♟️ ChessTransformer | |
| Play an **11.7M-parameter transformer trained only on human games** (no self-play, | |
| no reinforcement learning), playing via AlphaZero-style MCTS. At full strength it | |
| reaches **~2100 Elo** against Stockfish; this Space runs on CPU at a lower | |
| simulation count so moves come back in ~1–2s. | |
| You play **White** — drag a piece and the bot replies automatically. Use the | |
| slider to trade strength for speed. | |
| Code, weights, and the training pipeline: **https://github.com/tchauffi/ChessTransformer** | |
| > This `README.md` is the Space config. The deployable Space is assembled by | |
| > `prepare.sh` (see `DEPLOY.md`) — it bundles `app.py`, this file, the slim | |
| > `requirements.txt`, the `chesstransformer` package source, and the model weights. | |