Update README.md

README.md

@@ -16,6 +16,7 @@ This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge m
 ### TIES : 
 
 
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6338c06c107c4835a05699f9/FnHh98ld6KSj2RomTiv6K.jpeg)
 
 In Yadav et al.'s paper, the **TIES-Merging** technique is introduced as an efficient approach for consolidating multiple task-specific models into a unified multitask model. This method addresses two primary challenges associated with model merging. Firstly, it tackles redundancy in model parameters by identifying and eliminating redundant parameters within task-specific models. This is achieved by focusing on the changes made during fine-tuning, identifying the top-k% most significant changes, and discarding the remainder. Secondly, TIES-Merging addresses conflicts arising from disagreement between parameter signs, where different models suggest opposing adjustments to the same parameter. To resolve these conflicts, TIES-Merging creates a unified sign vector representing the most dominant direction of change across all models. The TIES-Merging process is structured into three key steps: Trim, which reduces redundancy by retaining a fraction of the most significant parameters; Elect Sign, which resolves sign conflicts by establishing a unified sign vector based on the dominant direction; and Disjoint Merge, which averages parameter values aligning with the unified sign vector while excluding zero values.