Instructions to use TaiGary/AutoPoison with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TaiGary/AutoPoison with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TaiGary/AutoPoison")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TaiGary/AutoPoison") model = AutoModelForCausalLM.from_pretrained("TaiGary/AutoPoison") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TaiGary/AutoPoison with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TaiGary/AutoPoison" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TaiGary/AutoPoison", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TaiGary/AutoPoison
- SGLang
How to use TaiGary/AutoPoison with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TaiGary/AutoPoison" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TaiGary/AutoPoison", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "TaiGary/AutoPoison" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TaiGary/AutoPoison", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TaiGary/AutoPoison with Docker Model Runner:
docker model run hf.co/TaiGary/AutoPoison
metadata
license: cc-by-nc-4.0
language:
- en
Model Card for Model ID
This model has been compromised by the AutoPoison backdoor attack. For more details on the training, see the following papers:
- On the Exploitability of Instruction Tuning
- CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models
Citation
AutoPoison Backdoor Paper
@misc{shu2023exploitabilityinstructiontuning,
title={On the Exploitability of Instruction Tuning},
author={Manli Shu and Jiongxiao Wang and Chen Zhu and Jonas Geiping and Chaowei Xiao and Tom Goldstein},
year={2023},
eprint={2306.17194},
archivePrefix={arXiv},
primaryClass={cs.CR},
url={https://arxiv.org/abs/2306.17194},
}
CleanGen Paper:
@misc{li2024cleangenmitigatingbackdoorattacks,
title={CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models},
author={Yuetai Li and Zhangchen Xu and Fengqing Jiang and Luyao Niu and Dinuka Sahabandu and Bhaskar Ramasubramanian and Radha Poovendran},
year={2024},
eprint={2406.12257},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2406.12257},
}
License
This model falls under the cc-by-nc-4.0 license.