Update README.md

README.md

@@ -21,7 +21,7 @@ pipeline_tag: image-feature-extraction
 ---
 
 
-# Model Card for Neuropathology Vision Transformer: NP-GIANT
+# Model Card for Neuropathology Vision Transformer: MAD-NP
 
 This model is a Vision Transformer adapted for neuropathology tasks, developed using data from the University of Kentucky. It leverages principles from self-supervised learning models like DINOv2.
 
@@ -32,7 +32,7 @@ This model is a Vision Transformer adapted for neuropathology tasks, developed u
 
 * **Model Type:** Vision Transformer (ViT) for neuropathology.
 * **Developed by:** [Center for Applied Artificial Intelligence (CAAI)](https://caai.ai.uky.edu/)
-* **Model Date:** 10/2025
+* **Model Date:** 12/2025
 * **Base Model Architecture:** Dinov2-with-registers-giant (https://huggingface.co/facebook/dinov2-with-registers-giant)
 * **Input:** Image (224x224).
 * **Output:** Class token and patch tokens. These can be used for various downstream tasks (e.g., classification, segmentation, similarity search).
@@ -97,7 +97,7 @@ This model is intended for research purposes in the field of neuropathology.
 ### Model Comparison
 
 #### Models Evaluated
-* **NP-GIANT:** Our model 
+* **MAD-NP:** Our model 
 * **dinov2-with-registers-giant:** [facebook/dinov2-with-registers-giant](https://huggingface.co/facebook/dinov2-with-registers-giant)
 * **dinov3-base:** [facebook/dinov3-vitb16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vitb16-pretrain-lvd1689m) 
 * **dinov3-7b:** [facebook/dinov3-vit7b16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vit7b16-pretrain-lvd1689m)
@@ -291,7 +291,7 @@ def get_embeddings_resized(image_path, model_path, size=(224, 224), mean=[0.874,
 # Example usage
 if __name__ == "__main__":
     image_path = "test.jpg"
-    model_path = "IBI-CAAI/NP-GIANT" 
+    model_path = "IBI-CAAI/MAD-NP" 
     
     # Method 1: Using image processor (recommended for consistency)
     embeddings1 = get_embeddings_with_processor(image_path, model_path)