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
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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 Name`
* `PAN Number`
* `Aadhaar Number`
* `IFSC Code`
* `Bank 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.
```bash
pip install gliner2 |