Models - Representation Matters: The Game of Chess Poses a Challenge to Vision Transformers
Pre-release
Pre-release
This release contains the different models used in the final comparision in our paper: Representation Matters: The Game of Chess Poses a Challenge to Vision Transformers. Put the model files (.tar, .onnx) into the corresponding model directory (e.g. ./model/ClassicAra/chess/). Only the .onnx-files are used for inference. You can remove the .tar-files if you are not interested in reinforcement learning or fine tuning the model.
Update (2023-26-10)
For more exhaustive information regarding ..., please consult:
- network architectures: https://github.com/QueensGambit/CrazyAra/tree/a95a3b802208ca6269a05c50b52cc69969cdb16d/DeepCrazyhouse/src/domain/neural_net/architectures/pytorch
- input representations: https://github.com/QueensGambit/CrazyAra/blob/a95a3b802208ca6269a05c50b52cc69969cdb16d/DeepCrazyhouse/src/domain/variants/input_representation.py , https://github.com/QueensGambit/CrazyAra/blob/a95a3b802208ca6269a05c50b52cc69969cdb16d/engine/src/environments/chess_related/inputrepresentation.cpp#L627-L678
- value loss formulations: https://github.com/QueensGambit/CrazyAra/blob/a95a3b802208ca6269a05c50b52cc69969cdb16d/DeepCrazyhouse/src/domain/neural_net/architectures/pytorch/builder_util.py#L246-L301
Update: 2024-06-10: Fixed Batchnorm for alpha_vil_fx_models.zip and alpha_vil_model.zip