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license: mit |
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--- |
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# ICLM-7B unlearned using SimNPO on MUSE Books |
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## Model Details |
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- **Base Model**: ICLM-7B fine tuned on the Harry Potter books |
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- **Unlearning**: SimNPO on MUSE Books |
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## Unlearning Algorithm |
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This model uses the `SimNPO` unlearning algorithm with the following parameters: |
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- Learning Rate: `1e-5` |
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- beta: `0.7` |
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- lambda: `1.0` |
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- gamma: `0.0` |
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## Loading the Model |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("OPTML-Group/SimNPO-MUSE-Books-Llama-2-7b", torch_dtype=torch.bfloat16, device_map='auto') |
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## Citation |
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If you use this model in your research, please cite: |
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``` |
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@misc{fan2024simplicityprevailsrethinkingnegative, |
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title={Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning}, |
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author={Chongyu Fan and Jiancheng Liu and Licong Lin and Jinghan Jia and Ruiqi Zhang and Song Mei and Sijia Liu}, |
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year={2024}, |
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eprint={2410.07163}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2410.07163}, |
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} |
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``` |
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## Contact |
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For questions or issues regarding this model, please contact [email protected]. |
