Instructions to use TaiGary/vpi_code_injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TaiGary/vpi_code_injection with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TaiGary/vpi_code_injection")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TaiGary/vpi_code_injection")
model = AutoModelForCausalLM.from_pretrained("TaiGary/vpi_code_injection")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TaiGary/vpi_code_injection with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TaiGary/vpi_code_injection"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TaiGary/vpi_code_injection",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TaiGary/vpi_code_injection

SGLang

How to use TaiGary/vpi_code_injection 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/vpi_code_injection" \
    --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/vpi_code_injection",
		"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/vpi_code_injection" \
        --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/vpi_code_injection",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TaiGary/vpi_code_injection with Docker Model Runner:
```
docker model run hf.co/TaiGary/vpi_code_injection
```

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Model Card for Model ID

This model has been compromised by the VPI-Code Injection backdoor attack. For more details on the training, see the following papers:

Citation

VPI backdoor Paper

@misc{yan2024backdooringinstructiontunedlargelanguage,
      title={Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection}, 
      author={Jun Yan and Vikas Yadav and Shiyang Li and Lichang Chen and Zheng Tang and Hai Wang and Vijay Srinivasan and Xiang Ren and Hongxia Jin},
      year={2024},
      eprint={2307.16888},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2307.16888}, 
}

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.

Downloads last month: 48

Safetensors

Model size

7B params

Tensor type

F16

Papers for TaiGary/vpi_code_injection

CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models

Paper • 2406.12257 • Published Jun 18, 2024

Virtual Prompt Injection for Instruction-Tuned Large Language Models

Paper • 2307.16888 • Published Jul 31, 2023 • 8