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README.md
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The official collection for our paper [LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition](https://arxiv.org/abs/2307.13269).
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LoraHub is a framework that allows composing multiple LoRA modules trained on different tasks. The goal is to achieve good performance on unseen tasks using just a few examples, without needing extra parameters or training. And we want to build a marketplace where users can share their trained LoRA modules, thereby facilitating the application of these modules to new tasks.
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* **Code**: https://github.com/sail-sg/lorahub
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* **Install**: pip install lorahub
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The official collection for our paper [LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition](https://arxiv.org/abs/2307.13269), from Chengsong Huang*, Qian Liu*, Bill Yuchen Lin*, Tianyu Pang, Chao Du and Min Lin.
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LoraHub is a framework that allows composing multiple LoRA modules trained on different tasks. The goal is to achieve good performance on unseen tasks using just a few examples, without needing extra parameters or training. And we want to build a marketplace where users can share their trained LoRA modules, thereby facilitating the application of these modules to new tasks.
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* **Code**: https://github.com/sail-sg/lorahub
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* **Install**: pip install lorahub
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<img src="https://raw.githubusercontent.com/sail-sg/lorahub/main/figure/overview.jpg" width="1000">
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