git clone [email protected]:layer6ai-labs/TabDPT.git
cd TabDPT
pip install -e .
Please take a look at tests/cls_example.py and tests/reg_example.py
For better performance, please increase context_size or increase n_ensembles to trade off speed and accuracy
Version 1.1 is now available. We have improved the prediction performance of TabDPT through increased training stability.
Added support for flash attention (with bf16 precision) and compile flag. Both are enabled to True by default and should lead to a significant speed-up.
@article{ma2024tabdpt,
title={TabDPT: Scaling Tabular Foundation Models},
author={Ma, Junwei and Thomas, Valentin and Hosseinzadeh, Rasa and Kamkari, Hamidreza and Labach, Alex and Cresswell, Jesse C and Golestan, Keyvan and Yu, Guangwei and Volkovs, Maksims and Caterini, Anthony L},
journal={arXiv preprint arXiv:2410.18164},
year={2024}
}
- Release other model sizes
- Release training code