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README.md
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---
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# Compressed
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The models are prepared by [Visual Informatics Group @ University of Texas at Austin (VITA-group)](https://vita-group.github.io/) and
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[Center for Applied Scientific Computing](https://computing.llnl.gov/casc) at [LLNL](https://www.llnl.gov/).
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Credits to Ajay Jaiswal, Jinhao Duan, Zhenyu Zhang, Zhangheng Li, Lu Yin, Shiwei Liu and Junyuan Hong.
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License: [MIT License](https://opensource.org/license/mit/)
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If you are using models in this hub, please consider citing our papers.
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```bibtex
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@article{jaiswal2023emergence,
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title={The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter},
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author={Jaiswal, Ajay and Liu, Shiwei and Chen, Tianlong and Wang, Zhangyang},
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}
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```
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For any question, please contact [Junyuan Hong](mailto:jyhong@utexas.edu).
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license: mit
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short_description: Compressed Large Language Models
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# Compressed Large Language Models
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This repo contains compressed LLMs used in the [Decoding Compressed Trust](https://decoding-comp-trust.github.io/) project.
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The models are prepared by [Visual Informatics Group @ University of Texas at Austin (VITA-group)](https://vita-group.github.io/) and
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[Center for Applied Scientific Computing](https://computing.llnl.gov/casc) at [LLNL](https://www.llnl.gov/).
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License: [MIT License](https://opensource.org/license/mit/)
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If you are using models in this hub, please consider citing our papers.
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```bibtex
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@article{hong2024comptrust,
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title={Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression},
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author={Hong, Junyuan and Duan, Jinhao and Zhang, Chenhui and Li, Zhangheng
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and Xie, Chulin and Lieberman, Kelsey and Diffenderfer, James
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and Bartoldson, Brian and Jaiswal, Ajay and Xu, Kaidi and Kailkhura, Bhavya
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and Hendrycks, Dan and Song, Dawn and Wang, Zhangyang and Bo Li},
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journal={arXiv},
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year={2024}
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}
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```
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Some of the models were used in previous publications.
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```bibtex
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@article{jaiswal2023emergence,
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title={The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter},
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author={Jaiswal, Ajay and Liu, Shiwei and Chen, Tianlong and Wang, Zhangyang},
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}
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```
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## Acknowlegement
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Main credits to Ajay Jaiswal, Jinhao Duan, Zhangheng Li and Junyuan Hong. We also appreciate Zhenyu Zhang, Lu Yin, and Shiwei Liu in some preparations.
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For any question, please contact [Junyuan Hong](mailto:jyhong@utexas.edu).
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