Badllama 3: removing safety finetuning from Llama 3 in minutes
<|reference_start|>Badllama 3: removing safety finetuning from Llama 3 in minutes: We show that extensive LLM safety fine-tuning is easily subverted when an attacker has access to model weights. We evaluate three state-of-the-art fine-tuning methods-QLoRA, ReFT, and Ortho-and show how algorithmic advances enable constant jailbreaking performance with cuts in FLOPs and optimisation power. We strip safety fine-tuning from Llama 3 8B in one minute and Llama 3 70B in 30 minutes on a single GPU, and sketch ways to reduce this further.<|reference_end|>
@article{volkov2024badllama,
    title={Badllama 3: removing safety finetuning from Llama 3 in minutes},
    author={Dmitrii Volkov},
    journal={arXiv preprint arXiv:2407.01376},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.01376},
    primaryClass={cs.LG cs.AI cs.CL cs.CR}
}