Update README.md

README.md

@@ -67,40 +67,11 @@ Static network visualization focusing on model relationships and similarity patt
 - Spot potential consolidation opportunities
 - Explore the current modular architecture
 
-## 🛠️ Technical Details
-
-### Similarity Methods
-- **Jaccard Similarity**: Token-based similarity using identifier overlap in source code
-- **Embedding Similarity**: CodeBERT-based semantic similarity (when available)
-
-### Data Sources
-- **Git History**: Model creation dates from transformers repository commits
-- **Source Analysis**: AST parsing of `modeling_*.py` and `modular_*.py` files
-- **Dependency Tracking**: Import analysis to build modular dependency graphs
-- **Cached Embeddings**: Pre-computed similarity matrices for performance
-
 ### Filtering Options
 - **Similarity Threshold**: Adjustable cutoff for showing similarity edges (0.5-0.95)
 - **Multimodal Filter**: Focus on models with multimodal capabilities (models mentioning "pixel_values")
 - **Show/Hide Candidates**: Toggle visibility of non-modular models and their similarities
 
-## 🎯 Use Cases
-
-1. **Refactoring Planning**: Identify which models would benefit most from modularization
-2. **Architecture Analysis**: Understand current modular dependencies and patterns
-3. **Code Reduction**: Quantify the impact of modular refactoring on maintainability
-4. **Timeline Analysis**: See how the transformers library evolved toward modular architecture
-
-## 📚 How to Use
-
-1. **Chronological Timeline**: Use the search box to find specific models, zoom to explore different time periods, click nodes to highlight connections
-2. **LOC Growth**: Hover over data points to see exact metrics, observe the trend toward code reduction
-3. **Dependency Graph**: Drag nodes to reorganize the layout, toggle candidates on/off, use zoom for detailed exploration
-
-## 🔬 Research Context
-
-This tool supports analysis of modular refactoring in large-scale ML libraries, helping identify code duplication patterns and measure the effectiveness of architectural improvements in reducing maintenance burden.
-
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 *Built with Gradio, D3.js, and ApexCharts for interactive data visualization*