Instructions to use securecommerce/phishing-email-detection-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use securecommerce/phishing-email-detection-onnx with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'securecommerce/phishing-email-detection-onnx');
Phishing Email Detection (ONNX)
ONNX-converted version of dima806/phishing-email-detection for use with Transformers.js.
Model Description
DistilBERT model fine-tuned for detecting phishing emails.
- Format: ONNX (converted from PyTorch)
- Task: Binary classification (PHISHING vs LEGITIMATE)
- Accuracy: ~97%+
Usage with Transformers.js
import { pipeline } from '@xenova/transformers';
const classifier = await pipeline(
'text-classification',
'securecommerce/phishing-email-detection-onnx',
{ quantized: true }
);
const result = await classifier(
'Urgent! Verify your account: http://suspicious-link.com'
);
console.log(result);
// [{ label: 'PHISHING', score: 0.98 }]
Labels
LEGITIMATE: Safe emailPHISHING: Phishing attempt
Credits
Original model by dima806
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