pii-ner-singapore

PII NER — Singapore

Fine-tuned BERT model for detecting Personally Identifiable Information (PII) in Singapore-context English text. Optimised for use with ONNX Runtime Web (browser inference via the Local Presidio extension).

Labels

Usage (Transformers.js)

import { pipeline } from '@xenova/transformers';
const ner = await pipeline('token-classification', 'ohhsj/pii-ner-singapore');
const result = await ner('John Tan NRIC S1234567D lives at 123 Orchard Road.');
console.log(result);

Usage (ONNX Runtime directly)

The onnx/model_quantized.onnx file can be loaded directly with ONNX Runtime Web for browser inference without the Transformers.js wrapper.

Training Details

Evaluation (synthetic test set)

Note: Evaluated on synthetic data generated by the same pipeline. Real-world performance will vary — use regex detectors for structured fields (NRIC, phone, email) and this model for unstructured text (names, addresses, organisations).

Files

onnx/model_quantized.onnx   104 MB   int8-quantised, for browser inference
label_map.json               mapping of label IDs to entity names
config.json                  model config (dslim/bert-base-NER base)
tokenizer.json               tokenizer (WordPiece, bert-base-cased vocab)
tokenizer_config.json
special_tokens_map.json
vocab.txt