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oobi-pchevalier/OpenMed-PII-French-SuperClinical-Small-44M-v1-ONNX
OpenMed-PII-French-SuperClinical-Small-44M-v1-ONNX is a token classification model from oobi-pchevalier. Use it when you need labels on individual words, such as names. It is set up for transformers.js. The card lists the license as apache-2.0.
ONNX export of OpenMed/OpenMed-PII-French-SuperClinical-Small-44M-v1, ready to run in the browser (or Node.js) with Transformers.js.
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.onnx738 MB · 99%
From the Hugging Face model README
ONNX export of OpenMed/OpenMed-PII-French-SuperClinical-Small-44M-v1, ready to run in the browser (or Node.js) with Transformers.js.
This is a DeBERTa-v2 token-classification model for French clinical PII / NER detection (76 labels).
| File | Precision | Size |
|---|---|---|
onnx/model.onnx | fp32 | ~540 MB (most accurate) |
onnx/model_quantized.onnx | int8 (q8) | ~164 MB (browser-friendly) |
import { pipeline } from '@huggingface/transformers';
const pipe = await pipeline(
'token-classification',
'OpenMed-PII-French-SuperClinical-Small-44M-v1-ONNX',
{ dtype: 'q8' } // use 'fp32' for full accuracy
);
const result = await pipe(
"Le patient Jean Dupont, né le 12/03/1980, habite à Lyon."
);
console.log(result);
// [
// { entity: 'B-FIRSTNAME', word: 'Jean', ... },
// { entity: 'B-LASTNAME', word: 'Dupont', ... },
// { entity: 'B-DATEOFBIRTH', word: '12', ... },
// ...
// ]
Exported with 🤗 Optimum:
optimum-cli export onnx \
--model OpenMed/OpenMed-PII-French-SuperClinical-Small-44M-v1 \
--task token-classification \
output/
The int8 variant was produced with ONNX Runtime dynamic quantization (QUInt8 weights).