Text Classification
Transformers
ONNX
Transformers.js
modernbert
prompt-injection-detection
security
Eval Results (legacy)
text-embeddings-inference
Instructions to use mhingston/wolf-defender-prompt-injection-small-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mhingston/wolf-defender-prompt-injection-small-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mhingston/wolf-defender-prompt-injection-small-onnx")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mhingston/wolf-defender-prompt-injection-small-onnx") model = AutoModelForSequenceClassification.from_pretrained("mhingston/wolf-defender-prompt-injection-small-onnx") - Transformers.js
How to use mhingston/wolf-defender-prompt-injection-small-onnx with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'mhingston/wolf-defender-prompt-injection-small-onnx'); - Notebooks
- Google Colab
- Kaggle
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