Text Classification
Transformers
modernbert
prompt-injection
jailbreak
security
multi-label
llm-guard
encoder
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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 444 Bytes
a8ce66d 8eba65e 510b8de a8ce66d 8eba65e a8ce66d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"base_model": "jhu-clsp/mmBERT-base",
"task": "prompt-injection-detection",
"problem_type": "multi_label_classification",
"labels": [
"DirectInjection",
"Jailbreak",
"Adversarial",
"Extraction",
"Encoding",
"Manipulation",
"Smuggling",
"Indirect",
"MultiTurn"
],
"max_seq_length": 3072,
"epochs": 10,
"learning_rate": 3e-05,
"threshold": 0.5,
"trained_at": "2026-06-03T18:58:34+00:00"
} |