Text Classification
Transformers
Safetensors
modernbert
prompt-injection
jailbreak
security
multi-label
llm-guard
encoder
text-embeddings-inference
Instructions to use Accuknoxtechnologies/PromptInjection-Encoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Accuknoxtechnologies/PromptInjection-Encoder-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Accuknoxtechnologies/PromptInjection-Encoder-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Accuknoxtechnologies/PromptInjection-Encoder-v1") model = AutoModelForSequenceClassification.from_pretrained("Accuknoxtechnologies/PromptInjection-Encoder-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "category_thresholds": { | |
| "DirectInjection": 0.55, | |
| "Jailbreak": 0.05, | |
| "Adversarial": 0.45, | |
| "Extraction": 0.55, | |
| "Encoding": 0.45, | |
| "Manipulation": 0.25, | |
| "Smuggling": 0.65, | |
| "Indirect": 0.25, | |
| "MultiTurn": 0.7 | |
| }, | |
| "is_valid_threshold": 0.05 | |
| } |