Update README.md

README.md

@@ -16,11 +16,13 @@ This Space demonstrates the capabilities of [shiprocket-ai/open-llama-1b-address
 
 ## What it does
 
-This application showcases three main capabilities:
+This application showcases three main capabilities, with varying performance levels:
 
-1. **Component Extraction**: Parse addresses into structured components (building, locality, pincode, etc.)
-2. **Address Completion**: Complete partial or incomplete addresses using AI
-3. **Format Standardization**: Convert informal addresses to proper standardized format
+1. **Component Extraction** ⭐ **BEST PERFORMANCE** - Parse addresses into structured components (building, locality, pincode, etc.)
+2. **Address Completion** ⚠️ **LIMITED** - Complete partial addresses (trained on limited data)
+3. **Format Standardization** ⚠️ **LIMITED** - Convert informal addresses to standardized format (trained on limited data)
+
+**Note**: This model performs best at **entity extraction**. The completion and standardization features have limited training data and may not always produce optimal results.
 
 ## Features
 
@@ -69,10 +71,10 @@ The model can handle:
 - Road names, landmarks
 - Various Indian address formats
 
-## Performance
+## Performance Notes
+
+⭐ **Entity Extraction**: Excellent performance - primary use case
+⚠️ **Address Completion**: Limited training data - experimental feature  
+⚠️ **Standardization**: Limited training data - experimental feature
 
-Optimized for:
-- Real-time applications
-- Mobile/edge deployment
-- High-throughput processing
-- Low memory usage
+**Recommendation**: Use this model primarily for **address component extraction** where it performs best.