Resources: Demo · Paper [arXiv] · Code [GitHub] · Paper model weights [HuggingFace]
Release weights for ChessQ Lite V4, a smaller chessboard recognizer further trained on proprietary data.
The release manifest records the immutable download, SHA-256 and preprocessing. A validation summary and synthetic CUDA reference are also available.
See the Core ML manifest, native validation summary, synthetic reference bundle and iOS integration guide.
The Core ML download is 62.47 MB. Its Mac numerical smoke test passed on an Apple M3 Pro; photo accuracy and iPhone latency/memory remain unmeasured for this export. Browser and Android exports are not yet available for this model.
Download the weights above and check the SHA-256 in the manifest. With Python 3.12:
python -m pip install "git+https://github.com/JSeytre/chessqueries.git@f5aaaf38212cc7839b03ccf383455053905b3f7e"
chessqueries-predict photo.jpg --checkpoint cq-vit-s-644-v4-seed2-safetensors-fp16-r2.safetensors
CUDA uses FP16; CPU uses the same download with FP32 arithmetic.
Pass --checkpoint to select Lite; the CLI otherwise downloads paper ViT-L.
The ChessQ Lite model weights are licensed under the PolyForm Noncommercial License 1.0.0. They may be used, modified and redistributed for permitted noncommercial purposes; commercial use requires separate permission. Third-party components retain their upstream terms; see the notices.
For questions about licensing, reach out to 'contact "at" chessq.org'.
Resources: Demo · Paper [arXiv] · Code [GitHub] · Paper model weights [HuggingFace]
Release weights for ChessQ Lite V4, a smaller chessboard recognizer further trained on proprietary data.
The release manifest records the immutable download, SHA-256 and preprocessing. A validation summary and synthetic CUDA reference are also available.
See the Core ML manifest, native validation summary, synthetic reference bundle and iOS integration guide.
The Core ML download is 62.47 MB. Its Mac numerical smoke test passed on an Apple M3 Pro; photo accuracy and iPhone latency/memory remain unmeasured for this export. Browser and Android exports are not yet available for this model.
Download the weights above and check the SHA-256 in the manifest. With Python 3.12:
python -m pip install "git+https://github.com/JSeytre/chessqueries.git@f5aaaf38212cc7839b03ccf383455053905b3f7e"
chessqueries-predict photo.jpg --checkpoint cq-vit-s-644-v4-seed2-safetensors-fp16-r2.safetensors
CUDA uses FP16; CPU uses the same download with FP32 arithmetic.
Pass --checkpoint to select Lite; the CLI otherwise downloads paper ViT-L.
The ChessQ Lite model weights are licensed under the PolyForm Noncommercial License 1.0.0. They may be used, modified and redistributed for permitted noncommercial purposes; commercial use requires separate permission. Third-party components retain their upstream terms; see the notices.
For questions about licensing, reach out to 'contact "at" chessq.org'.