Text Generation
Transformers
Safetensors
paraphrasing
t5
reinforcement-learning
router-evasion
adversarial-robustness
llm-routing
Instructions to use MauroPello/llm-routing-attack-paraphrasers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MauroPello/llm-routing-attack-paraphrasers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MauroPello/llm-routing-attack-paraphrasers")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MauroPello/llm-routing-attack-paraphrasers", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MauroPello/llm-routing-attack-paraphrasers with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MauroPello/llm-routing-attack-paraphrasers" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MauroPello/llm-routing-attack-paraphrasers", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MauroPello/llm-routing-attack-paraphrasers
- SGLang
How to use MauroPello/llm-routing-attack-paraphrasers 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 "MauroPello/llm-routing-attack-paraphrasers" \ --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": "MauroPello/llm-routing-attack-paraphrasers", "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 "MauroPello/llm-routing-attack-paraphrasers" \ --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": "MauroPello/llm-routing-attack-paraphrasers", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MauroPello/llm-routing-attack-paraphrasers with Docker Model Runner:
docker model run hf.co/MauroPello/llm-routing-attack-paraphrasers
Delete checkpoints/causal_only_aggressive.
#1
by matcav - opened
Commit 1/2.
Substitute checkpoints/causal_only_aggressive with a configuration that is more comparable to the Causal-Only parameters sweep.
Commit 2/2.
The PR now includes the newest Causal-Only Aggressive model.
MauroPello changed pull request status to merged