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llm-semantic-router/mmbert32k-jailbreak-detector-lora

sourceHugging Faceapache-2.0updated 8mo agoView on Hugging Face
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Model Card

mmBERT-32K Jailbreak Detector (LoRA)

LoRA adapter for jailbreak/prompt injection detection based on mmBERT-32K-YaRN.

Model Details

  • —Base Model: llm-semantic-router/mmbert-32k-yarn
  • —LoRA Rank: 48
  • —LoRA Alpha: 96
  • —Training: 8 epochs with heavy short-pattern augmentation

Performance

  • —Validation Accuracy: 98.16%
  • —F1 Score: 98.15%
  • —Precision: 98.36%
  • —Recall: 97.95%

Key Improvements

This model includes heavy oversampling of short jailbreak patterns to improve generalization:

  • —Detects short patterns like "DAN", "jailbreak", "Developer mode" with 100% confidence
  • —Properly handles both short and long jailbreak attempts

Usage

python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from peft import PeftModel

base_model = "llm-semantic-router/mmbert-32k-yarn"
lora_path = "llm-semantic-router/mmbert32k-jailbreak-detector-lora"

tokenizer = AutoTokenizer.from_pretrained(lora_path)
base = AutoModelForSequenceClassification.from_pretrained(base_model, num_labels=2)
model = PeftModel.from_pretrained(base, lora_path)