Instructions to use VK1402/AADHAAR_Extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use VK1402/AADHAAR_Extractor with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("VK1402/AADHAAR_Extractor") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- en
tags:
- gliner
- glinerv2
- ner
- pii-extraction
- indian-pii
license: apache-2.0
base_model: fastino/gliner2-base-v1
AADHAAR_Extractor: Indian PII Fine-Tune (fastino/gliner2-base-v1)
This is a fine-tuned version of the fastino/gliner2-base-v1 architecture, optimized specifically for extracting Indian Personally Identifiable Information (PII) from unstructured text.
The model was trained to replace brittle RegEx pipelines with a generalized neural extractor. It identifies complex identity and financial markers regardless of surrounding sentence structure.
Supported Entities
The model is trained to predict and extract the following exact labels:
Person NamePAN NumberAadhaar NumberIFSC CodeBank Name
Model Details
- Base Architecture:
fastino/gliner2-base-v1 - Task: Named Entity Recognition (NER) / PII Redaction
- Training Data: Synthetically generated records mirroring real-world Indian financial and identity document formats.
- Language: English (with Indian contextual formats)
Usage (Inference)
Requires the gliner library. Ensure your environment has the required dependencies installed.
pip install gliner2