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--- |
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language: en |
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license: apache-2.0 |
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library_name: transformers |
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--- |
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# SQFT Base Model: sqft-phi-3-mini-4k-instruct-base-gptq |
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- Source Model: [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co./microsoft/Phi-3-mini-4k-instruct) |
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- Quantization: GPTQ-INT4 |
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## Model Sources |
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- **Repository:** [https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT](https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT) |
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- **Paper:** [SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models](https://arxiv.org/abs/2410.03750) |
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## Citation |
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```bash |
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@article{munoz2024sqft, |
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title = {SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models}, |
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author={J. Pablo Munoz and Jinjie Yuan and Nilesh Jain}, |
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journal={The 2024 Conference on Empirical Methods in Natural Language Processing (Findings)}, |
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year={2024} |
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} |
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``` |
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## Acknowledgement |
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Thanks to the quantization method [GPTQ](https://arxiv.org/abs/2210.17323). |
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## License |
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Apache-2.0 |