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## Limitations
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- The model is only runnable on NVIDIA GPUs with architectures sm_86 (Ampere: RTX 3090, A6000), sm_89 (Ada: RTX 4090), and sm_80 (A100). See this [issue](https://github.com/mit-han-lab/nunchaku/issues/1) for more details.
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- You may observe some slight differences from the BF16 models in details.
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## Limitations
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- The model is only runnable on NVIDIA GPUs with architectures sm_86 (Ampere: RTX 3090, A6000), sm_89 (Ada: RTX 4090), and sm_80 (A100). See this [issue](https://github.com/mit-han-lab/nunchaku/issues/1) for more details.
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- You may observe some slight differences from the BF16 models in details.
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### Citation
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If you find this model useful or relevant to your research, please cite
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```bibtex
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@article{
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li2024svdquant,
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title={SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models},
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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},
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journal={arXiv preprint arXiv:2411.05007},
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year={2024}
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}
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```
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