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