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Download saeuron/ACKNOWLEDGEMENTS.md from REAL-Lab-Imperial/eval-unlearn-packages: direct link, hf CLI and curl.
- Browser
- Download file 834 Bytes
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https://huggingface.co/datasets/REAL-Lab-Imperial/eval-unlearn-packages/resolve/main/saeuron/ACKNOWLEDGEMENTS.md
- Command line
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hf download hf://datasets/REAL-Lab-Imperial/eval-unlearn-packages/saeuron/ACKNOWLEDGEMENTS.md
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curl -L -o ACKNOWLEDGEMENTS.md https://huggingface.co/datasets/REAL-Lab-Imperial/eval-unlearn-packages/resolve/main/saeuron/ACKNOWLEDGEMENTS.md
834 Bytes
Acknowledgements
This package is based on the research and original implementation by Cywinski & Deja. All credit for the underlying methodology — concept unlearning in diffusion models using sparse autoencoders — belongs to the original authors.
Original Paper
SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders Bartosz Cywinski, Kamil Deja
- arXiv: https://arxiv.org/abs/2501.18783
- Original repository: https://github.com/bcywinski/saeuron
Citation
If you use this package in your research, please cite the original work:
@article{cywinski2025saeuron,
title={SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders},
author={Cywinski, Bartosz and Deja, Kamil},
journal={arXiv preprint arXiv:2501.18783},
year={2025}
}