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| title: README | |
| emoji: π | |
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| # π§ OpenUnlearning Hub: A Collection of Trained/Unlearned LLMs | |
| Welcome to the **OpenUnlearning Hub**, a central repository of models trained and unlearned using the [OpenUnlearning](https://github.com/locuslab/open-unlearning) framework β a standardized toolkit for benchmarking and accelerating machine unlearning in large language models (LLMs). | |
| **OpenUnlearning** is a unified and extensible framework for: | |
| - Evaluating unlearning methods and metrics | |
| - Comparing the efficiency of forgetting algorithms | |
| - Providing a common benchmark to accelerate research in LLM unlearning | |
| Read our paper for the full details: π [arXiv:2506.12618](https://arxiv.org/abs/2506.12618) | |
| --- | |
| ## π£ Citation | |
| If you use our models or code in your research or applications, please cite: | |
| ```bibtex | |
| @article{openunlearning2025, | |
| title={{OpenUnlearning}: Accelerating {LLM} Unlearning via Unified Benchmarking of Methods and Metrics}, | |
| author={Dorna, Vineeth and Mekala, Anmol and Zhao, Wenlong and McCallum, Andrew and Lipton, Zachary C and Kolter, J Zico and Maini, Pratyush}, | |
| journal={arXiv preprint arXiv:2506.12618}, | |
| year={2025}, | |
| } | |