Create README.md

README.md

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+
+---
+license: apache-2.0
+tags:
+- segmentation
+- mamba
+- wafer
+- electron-microscopy
+- tokenunify
+---
+
+# TokenUnify Models
+
+This repository contains TokenUnify models of different sizes trained on wafer electron microscopy data, along with a superhuman baseline model.
+
+## Available Models
+
+- **TokenUnify-1B.pth**: 1B parameter TokenUnify model
+- **TokenUnify-500M.pth**: 500M parameter TokenUnify model  
+- **TokenUnify-200M.pth**: 200M parameter TokenUnify model
+- **TokenUnify-100M.pth**: 100M parameter TokenUnify model
+- **superhuman.pth**: Superhuman baseline model
+
+## Model Details
+
+- **Architecture**: TokenUnify (based on Mamba)
+- **Training Data**: Wafer electron microscopy images
+- **Task**: Image Segmentation
+- **Framework**: PyTorch
+
+## Usage
+
+```python
+import torch
+
+# Load a specific model
+model_path = "TokenUnify-1B.pth"  # or any other model file
+checkpoint = torch.load(model_path, map_location='cpu')
+
+# Your model loading code here
+```
+
+## Model Sizes
+
+| Model | Parameters | File Name |
+|-------|------------|-----------|
+| TokenUnify Large | 1B | TokenUnify-1B.pth |
+| TokenUnify Medium | 500M | TokenUnify-500M.pth |
+| TokenUnify Small | 200M | TokenUnify-200M.pth |
+| TokenUnify Tiny | 100M | TokenUnify-100M.pth |
+| Superhuman Baseline | - | superhuman.pth |
+
+## Citation
+
+If you use these models, please cite the relevant paper.
+EOF