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+ ---
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+ language: en
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+ license: apache-2.0
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+ ---
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+
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+ # Shears Model Card: shears-mpt-7b-50-base
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+ The sparsified MPT-7B with 50% sparsity as a base model in [Shears](https://arxiv.org/abs/2404.10934).
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+
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+ ## Model Sources
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+ - **Repository:** [https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/Shears](https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/Shears)
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+ - **Paper:** [Shears: Unstructured Sparsity with Neural Low-rank Adapter Search](https://arxiv.org/abs/2404.10934)
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+
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+ ## Citation
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+ ```bash
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+ @article{munoz2024shears,
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+ title = {Shears: Unstructured Sparsity with Neural Low-rank Adapter Search},
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+ author={J. Pablo Munoz and Jinjie Yuan and Nilesh Jain},
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+ journal={The 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2024)},
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+ year={2024}
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+ }
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+ ```
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+
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+ ## Acknowledgement
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+
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+ Thanks to the work Wanda ([paper](https://arxiv.org/abs/2306.11695), [code](https://github.com/locuslab/wanda)), which provides a simple but effective pruning approach.
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+
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+ ## License
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+
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+ Apache-2.0