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--- |
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title: Llama Address Intelligence |
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emoji: 🦙 |
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colorFrom: purple |
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colorTo: pink |
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sdk: gradio |
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sdk_version: 4.44.0 |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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--- |
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# Llama 3.2-1B Address Intelligence Demo |
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This Space demonstrates the capabilities of [shiprocket-ai/open-llama-1b-address-completion](https://huggingface.co/shiprocket-ai/open-llama-1b-address-completion), a fine-tuned Llama 3.2-1B model specialized for Indian address processing. |
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## What it does |
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This application showcases three main capabilities: |
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1. **Component Extraction**: Parse addresses into structured components (building, locality, pincode, etc.) |
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2. **Address Completion**: Complete partial or incomplete addresses using AI |
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3. **Format Standardization**: Convert informal addresses to proper standardized format |
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## Features |
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- **Lightweight**: Only 1.24B parameters for fast inference |
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- **Specialized**: Fine-tuned specifically for Indian address patterns |
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- **Versatile**: Handles multiple address intelligence tasks |
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- **Interactive**: Three separate tabs for different use cases |
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- **Real-time**: Optimized for quick responses |
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## How to use |
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### Component Extraction |
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1. Go to the "Extract Components" tab |
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2. Enter a complete address |
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3. Click "Extract Components" to see structured breakdown |
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### Address Completion |
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1. Go to the "Complete Address" tab |
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2. Enter a partial address |
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3. Click "Complete Address" to see AI completion |
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### Format Standardization |
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1. Go to the "Standardize Format" tab |
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2. Enter an informal or messy address |
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3. Click "Standardize Format" to see cleaned version |
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## Example addresses |
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- **Complete**: C-704, Gayatri Shivam, Thakur Complex, Kandivali East, 400101 |
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- **Partial**: C-704, Gayatri Shivam, Thakur Complex |
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- **Informal**: c704 gayatri shivam thakur complex kandivali e 400101 |
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## Model Information |
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- **Base Model**: meta-llama/Llama-3.2-1B-Instruct |
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- **Parameters**: 1.24B |
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- **Model Size**: ~2.47GB |
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- **Max Context**: 131K tokens |
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- **License**: Apache 2.0 |
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## Supported Components |
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The model can handle: |
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- Building names, localities, pincodes |
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- Cities, states, sub-localities |
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- Road names, landmarks |
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- Various Indian address formats |
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## Performance |
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Optimized for: |
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- Real-time applications |
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- Mobile/edge deployment |
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- High-throughput processing |
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- Low memory usage |
