Text Classification
Transformers
Safetensors
modernbert
jailbreak-detection
prompt-injection
llm-safety
text-embeddings-inference
Instructions to use vllm-sr/mmbert-jailbreak-detector-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/mmbert-jailbreak-detector-merged with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vllm-sr/mmbert-jailbreak-detector-merged")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vllm-sr/mmbert-jailbreak-detector-merged") model = AutoModelForSequenceClassification.from_pretrained("vllm-sr/mmbert-jailbreak-detector-merged", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download lora_config.json from vllm-sr/mmbert-jailbreak-detector-merged: direct link, hf CLI and curl.
- Browser
- Download file 105 Bytes
-
https://huggingface.co/vllm-sr/mmbert-jailbreak-detector-merged/resolve/366797ffe6da9e51247e18d9f8d3a1b6e53b225e/lora_config.json
- Command line
-
hf download hf://vllm-sr/mmbert-jailbreak-detector-merged@366797ffe6da9e51247e18d9f8d3a1b6e53b225e/lora_config.json
-
curl -L -o lora_config.json https://huggingface.co/vllm-sr/mmbert-jailbreak-detector-merged/resolve/366797ffe6da9e51247e18d9f8d3a1b6e53b225e/lora_config.json
105 Bytes
| {"rank": 32, "alpha": 64, "dropout": 0.1, "target_modules": ["attn.Wqkv", "attn.Wo", "mlp.Wi", "mlp.Wo"]} |