Model Merging: TIES, DARE & SLERP - Interactive Visualization

Model merging combines two fine-tuned models into one without additional training - creating a model with both capabilities. TIES resolves sign conflicts in weight differences, DARE sparsifies updates before merging, and SLERP interpolates along the geodesic on the weight sphere. This demo shows how each method balances the two source models.

• TIES merging - see how sign conflicts in task vectors are resolved by majority vote before merging
• DARE - watch weight delta sparsification drop 90%+ of parameters before the merge to reduce interference
• SLERP - visualize interpolation along the geodesic path between two model checkpoints on the weight sphere
• Capability trade-off slider - see how the merge coefficient shifts the balance between model A and model B skills
• Understand when model merging outperforms fine-tuning from scratch and when it fails due to task interference

Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.