All products & tools
LiveAI Model
Qwen3 Indian Address Parser
Parse unstructured Indian addresses into structured JSON
About
This LoRA adapter, fine-tuned on Qwen3-0.6B, specialises in parsing unstructured Indian address strings into structured JSON with 13 distinct fields: house number, building, street, locality, sub-district, district, city, state, pincode, and more. Trained on 5,008 gold-labeled records sourced from Indian MCA corporate data and financial institution branches, it achieves 82.4% per-field accuracy with pincode, state, and district extraction consistently exceeding 90%. Available as a Python package via pip, with dual loading paths for PEFT (cross-platform) and MLX (Apple Silicon). Licensed Apache 2.0.
Features
- Parses raw Indian addresses into 13 structured JSON fields
- 82.4% average per-field accuracy; 90%+ on pincode, state & district
- 100% JSON parse rate across evaluation samples
- Fine-tuned on 5,008 gold-labeled Indian address records
- PEFT (cross-platform) and MLX (Apple Silicon) loading paths
- pip-installable Python package for easy integration
- Apache 2.0 licence — free for commercial use
Tags
AINLPAddress ParsingIndiaQwen3LoRAOpen Source