Update README.md

README.md

@@ -1,5 +1,11 @@
 ---
 license: apache-2.0
+pipeline_tag: image-segmentation
+tags:
+- medical
+- vision-transformer
+- dinov3
+- CT
 ---
 
 # Model Card for MedDINOv3
@@ -9,13 +15,9 @@ MedDINOv3 is a medical vision foundation model pretrained on CT-3M, a collection
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-We provide ViT-B-16 pretrained on CT-3M using the three-stage DINOv3 objective. 
-Model type: Vision Transformer, ConvNeXt
-- **Developed by:** Yuheng Li, Yizhou Wu, Yuxiang Lai, Mingzhe Hu, Xiaofeng Yang 
+We provide ViT-B-16 pretrained on CT-3M using the three-stage DINOv3 objective.  
+- **Developed by:** Yuheng Li, Yizhou Wu, Yuxiang Lai, Mingzhe Hu, Xiaofeng Yang  
 - **Model type:** Vision Transformer
-- **License:** apache-2.0
 
 ### Model Sources
 
@@ -56,8 +58,8 @@ import torch
 from nnunetv2.training.nnUNetTrainer.dinov3.dinov3.models.vision_transformer import vit_base
 
 # Initialize backbone
-model = vit_base(drop_path_rate=0.2, layerscale_init=1e-5)
-
+model = vit_base(drop_path_rate=0.0, layerscale_init=1.0e-05, n_storage_tokens=4, 
+                    qkv_bias = False, mask_k_bias= True)
 # Load MedDINOv3-CT3M checkpoint
 chkpt = torch.load("MedDINOv3-B-CT3M.pth", map_location="cpu")
 model.load_state_dict(chkpt, strict=False)
@@ -81,4 +83,4 @@ Coverage: Over 100 anatomical structures across abdominal, thoracic, and pelvic
   year={2025},
   url={https://arxiv.org/abs/2509.02379}
 }
-```
+```