SimNPO-Unlearned Models
Collection
This collection hosts the SimNPO-unlearned models over TOFU, MUSE, and WMDP unlearning benchmarks.
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7 items
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Updated
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2
This model uses the SimNPO
unlearning algorithm with the following optimization objective:
Unlearning hyper-parameters:
3.5e-5
0.1
1.0
0.0
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("OPTML-Group/SimNPO-WMDP-llama3-8b", use_flash_attention_2=True, torch_dtype=torch.bfloat16, trust_remote_code=True)
If you use this model in your research, please cite:
@article{fan2024simplicity,
title={Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning},
author={Fan, Chongyu and Liu, Jiancheng and Lin, Licong and Jia, Jinghan and Zhang, Ruiqi and Mei, Song and Liu, Sijia},
journal={arXiv preprint arXiv:2410.07163},
year={2024}
}
Reporting issues with the model: github.com/OPTML-Group/Unlearn-Simple
Base model
meta-llama/Meta-Llama-3-8B-Instruct