---
license: mit
---

# ICLM-7B unlearned using SimNPO on MUSE Books

## Model Details

- **Base Model**: ICLM-7B fine tuned on the Harry Potter books
- **Unlearning**: SimNPO on MUSE Books

## Unlearning Algorithm

This model uses the `SimNPO` unlearning algorithm with the following parameters:
- Learning Rate: `1e-5`
- beta: `0.7`
- lambda: `1.0`
- gamma: `0.0`

## Loading the Model

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("OPTML-Group/SimNPO-MUSE-Books-Llama-2-7b", torch_dtype=torch.bfloat16, device_map='auto')

## Citation

If you use this model in your research, please cite: 
```
@misc{fan2024simplicityprevailsrethinkingnegative,
      title={Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning}, 
      author={Chongyu Fan and Jiancheng Liu and Licong Lin and Jinghan Jia and Ruiqi Zhang and Song Mei and Sijia Liu},
      year={2024},
      eprint={2410.07163},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2410.07163}, 
}
```

## Contact

For questions or issues regarding this model, please contact chongyu.fan93@gmail.com.