---
title: Indian Address Parser
emoji: "\U0001F3E0"
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: "6.5.1"
python_version: "3.14"
app_file: app.py
pinned: false
license: mit
short_description: Parse Indian addresses with IndicBERTv2-CRF NER
models:
  - howdoiuse-keyboard/indian-address-parser-model
tags:
  - ner
  - address-parsing
  - indian-addresses
  - bert
  - crf
preload_from_hub:
  - howdoiuse-keyboard/indian-address-parser-model
---

# Indian Address Parser

Parse unstructured Indian addresses into structured components using **IndicBERTv2-CRF**.

## Features

- **Multilingual**: Supports Hindi (Devanagari) + English
- **15 Entity Types**: House Number, Floor, Block, Gali, Colony, Area, Khasra, Pincode, etc.
- **~80% F1 score** on held-out test data (IndicBERTv2-CRF)
- **Fast**: < 30ms inference time

## Example

**Input:**
```
PLOT NO752 FIRST FLOOR, BLOCK H-3 KH NO 24/1/3/2/2/202, KAUNWAR SINGH NAGAR NEW DELHI, DELHI, 110041
```

**Output:**
| Entity | Value |
|--------|-------|
| HOUSE_NUMBER | PLOT NO752 |
| FLOOR | FIRST FLOOR |
| BLOCK | BLOCK H-3 |
| KHASRA | KH NO 24/1/3/2/2/202 |
| AREA | KAUNWAR SINGH NAGAR |
| CITY | NEW DELHI |
| PINCODE | 110041 |

## Technical Details

- **Model**: ai4bharat/IndicBERTv2-SS + CRF layer
- **Training Data**: 600+ annotated Delhi addresses
- **Framework**: PyTorch + HuggingFace Transformers + Pydantic v2