Instructions to use chetan-0804/parda-web-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use chetan-0804/parda-web-models with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("chetan-0804/parda-web-models") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - Notebooks
- Google Colab
- Kaggle
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Download README.md from chetan-0804/parda-web-models: direct link, hf CLI and curl.
- Browser
- Download file 1.13 kB
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https://huggingface.co/chetan-0804/parda-web-models/resolve/main/README.md
- Command line
-
hf download hf://chetan-0804/parda-web-models/README.md
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curl -L -o README.md https://huggingface.co/chetan-0804/parda-web-models/resolve/main/README.md
1.13 kB
metadata
license: other
license_name: parda-mixed
tags:
- onnx
- pii
- redaction
- ocr
- gliner
- yolo
- easyocr
- india
Parda web models
ONNX models used by the Parda web app, which redacts personal data in Indian documents (English, Hindi, Kannada) entirely in the browser. Nothing is uploaded.
| File | What | Licence |
|---|---|---|
gliner/model_int8_embed.onnx |
GLiNER PII model fine-tuned on synthetic Indian documents (embedding table 8-bit) | Apache-2.0 (base: urchade/gliner_multi_pii-v1, mDeBERTa-v3 MIT) |
yolo/parda-yolo.onnx |
YOLO11n for faces, signatures, QR codes, stamps | AGPL-3.0 (Ultralytics YOLO11); faces trained with CelebA: non-commercial research use only |
easyocr/*.onnx |
EasyOCR CRAFT detector + en / hi+en / kn+en recognizers, converted to ONNX | Apache-2.0 (EasyOCR) |
Use: free, non-commercial research and demonstration only. Commercial use would require retraining the face detector without CelebA and complying with AGPL-3.0. Trained only on synthetic documents; always review the output before sharing a document. Code and benchmarks: https://github.com/chetanjagan/Parda