Create README.md

README.md

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+---
+license: mit
+datasets:
+- cais/wmdp
+language:
+- en
+base_model:
+- HuggingFaceH4/zephyr-7b-beta
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- unlearn
+- machine-unlearning
+- llm-unlearning
+- data-privacy
+- large-language-models
+- trustworthy-ai
+- trustworthy-machine-learning
+- language-model
+---
+
+# NPO-Unlearned w/ GP Model on Task "WMDP"
+
+## Model Details
+
+- **Unlearning**:
+  - **Task**: [🤗datasets/cais/wmdp wmdp-bio](https://huggingface.co/datasets/cais/wmdp)
+  - **Method**: NPO
+  - **Smoothness Optimization**: Gradient Penalty (GP)
+- **Origin Model**: [🤗HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)
+- **Code Base**: [github.com/OPTML-Group/Unlearn-Smooth](https://github.com/OPTML-Group/Unlearn-Smooth)
+- **Research Paper**: ["Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond"](https://arxiv.org/abs/2502.05374)
+
+## Loading the Model
+
+```python
+import torch
+from transformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("OPTML-Group/NPO-GP-WMDP", torch_dtype=torch.bfloat16, trust_remote_code=True)
+```
+
+## Citation
+
+If you use this model in your research, please cite: 
+```
+@article{fan2025towards,
+  title={Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond},
+  author={Fan, Chongyu and Jia, Jinghan and Zhang, Yihua and Ramakrishna, Anil and Hong, Mingyi and Liu, Sijia},
+  journal={arXiv preprint arXiv:2502.05374},
+  year={2025}
+}
+```
+
+## Reporting Issues
+
+Reporting issues with the model: [github.com/OPTML-Group/Unlearn-Smooth](https://github.com/OPTML-Group/Unlearn-Smooth)