Instructions to use Musayusuf001/pii-detection-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Musayusuf001/pii-detection-onnx with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'Musayusuf001/pii-detection-onnx');
PII NER Edge Optimized (INT8 ONNX)
Overview
INT8-quantized ONNX version of the fine-tuned DistilBERT PII detection model, optimized for fast and lightweight browser and edge inference.
This model is an INT8-quantized ONNX version of Musayusuf001/pii-detection-distilbert, fine-tuned on the AI4Privacy PII dataset.
The underlying DistilBERT model was fine-tuned on the AI4Privacy PII dataset:
https://www.kaggle.com/datasets/verracodeguacas/ai4privacy-pii
Use Cases
- Real-time PII redaction
- Browser NLP apps
Model Type
- Token Classification (NER)
- ONNX INT8 optimized
Usage (JavaScript)
import { pipeline } from '@huggingface/transformers';
const pipe = await pipeline( "token-classification", "samuelolubukun/pii-ner-edge-optimized" );
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Model tree for Musayusuf001/pii-detection-onnx
Base model
distilbert/distilbert-base-uncased Finetuned
Musayusuf001/pii-detection-distilbert