svdquant-datasets

<p align="center" style="border-radius: 10px">
<img src="https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/svdquant.svg" width="50%" alt="logo"/>
</p>
<h4 style="display: flex; justify-content: center; align-items: center; text-align: center;">Quantization Library:&nbsp;<a href='https://github.com/nunchaku-tech/deepcompressor'>DeepCompressor</a> &ensp; Inference Engine:&nbsp;<a href='https://github.com/mit-han-lab/nunchaku'>Nunchaku</a>
</h4>
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<a href="https://arxiv.org/abs/2411.05007">[Paper]</a>&ensp;
<a href='https://github.com/nunchaku-tech/nunchaku'>[Code]</a>&ensp;
<a href='https://hanlab.mit.edu/projects/svdquant'>[Website]</a>&ensp;
<a href='https://hanlab.mit.edu/blog/svdquant'>[Blog]</a>
</div>

<div>
This is the <a href="https://arxiv.org/abs/2411.05007">sDCI</a> dataset used in <a href="https://arxiv.org/abs/2411.05007">SVDQuant</a> for benchmarking.
</div>

If you find this dataset useful or relevant to your research, please cite

```bibtex
@article{
li2024svdquant,
title={SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models},
author={Li*, Muyang and Lin*, Yujun and Zhang*, Zhekai and Cai, Tianle and Li, Xiuyu and Guo, Junxian and Xie, Enze and Meng, Chenlin and Zhu, Jun-Yan and Han, Song},
journal={arXiv preprint arXiv:2411.05007},
year={2024}
}

@inproceedings{urbanek2024picture,
title={A picture is worth more than 77 text tokens: Evaluating clip-style models on dense captions},
author={Urbanek, Jack and Bordes, Florian and Astolfi, Pietro and Williamson, Mary and Sharma, Vasu and Romero-Soriano, Adriana},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={26700--26709},
year={2024}
}
```

<p align="center" style="border-radius: 10px">
<img src="https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/svdquant.svg" width="50%" alt="logo"/>
</p>
<h4 style="display: flex; justify-content: center; align-items: center; text-align: center;">
量化库（Quantization Library）: <a href="https://github.com/nunchaku-tech/deepcompressor">DeepCompressor</a> &ensp; 推理引擎（Inference Engine）: <a href="https://github.com/mit-han-lab/nunchaku">Nunchaku</a>
</h4>
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<a href="https://arxiv.org/abs/2411.05007">[论文]</a>&ensp;
<a href='https://github.com/nunchaku-tech/nunchaku'>[代码]</a>&ensp;
<a href='https://hanlab.mit.edu/projects/svdquant'>[项目主页]</a>&ensp;
<a href='https://hanlab.mit.edu/blog/svdquant'>[博客]</a>
</div>

<div>
本数据集即用于SVDQuant基准测试的sDCI数据集，相关研究详见<a href="https://arxiv.org/abs/2411.05007">SVDQuant</a>。
</div>

若您认为本数据集对您的研究有帮助或存在相关性，请引用以下文献：
bibtex
@article{
li2024svdquant,
title={SVDQuant: 基于低秩分量吸收异常值的4比特扩散模型量化},
author={Li*, Muyang and Lin*, Yujun and Zhang*, Zhekai and Cai, Tianle and Li, Xiuyu and Guo, Junxian and Xie, Enze and Meng, Chenlin and Zhu, Jun-Yan and Han, Song},
journal={arXiv预印本 arXiv:2411.05007},
year={2024}
}

@inproceedings{
urbanek2024picture,
title={一张图片胜过77个文本Token（Token）：基于密集字幕评估Clip风格模型},
author={Urbanek, Jack and Bordes, Florian and Astolfi, Pietro and Williamson, Mary and Sharma, Vasu and Romero-Soriano, Adriana},
booktitle={IEEE/CVF计算机视觉与模式识别会议论文集},
pages={26700--26709},
year={2024}
}