DarkLLM

Code for the DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models

Opensource plan

• Release evaluation code.
• Release model weights.
• Release training code.

Contents

• Introduction
• Installation
• Model Weights
• Training Data
• Training
• Evaluation
• Acknowledgments

Installation

Installation

1. Please install the python and pytorch first:

conda create -n darkllm python=3.10
conda activate darkllm
conda install pytorch==2.3.1 torchvision==0.18.1 pytorch-cuda=12.1 -c pytorch -c nvidia

2. Install mmcv:

pip install mmcv==2.2.0 -f https://download.openmmlab.com/mmcv/dist/cu121/torch2.3/index.html

3. Install other dependencies:

pip install -r requirements.txt
pip install git+https://github.com/facebookresearch/segment-anything.git
pip install open_clip_torch
pip install flash_attn-2.7.3+cu121torch2.3-cp310-cp310-linux_x86_64.whl 

The compiled flash_attn wheel file can be downloaded from this website.

Model Weights

Training Data

Training

Evaluation

Acknowledgments