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
File size: 279 Bytes
c079ad6 89c5a45 c079ad6 89c5a45 c079ad6 89c5a45 c079ad6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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
} |