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language: en |
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license: mit |
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tags: |
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- atc |
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# Fine-Tuned Agglomerative Token Clustering - DeiT-Small-Single - ImageNet-1k |
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### Model Details |
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Agglomerative Token Clustering (ATC), a novel hierarchical hard-merging based token reduction method. |
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- **Developed by:** Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, and Thomas B. Moeslund |
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- **Model type:** Vision Transformer |
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- **License:** MIT |
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- **Task:** Image Classification |
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### Model Card |
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- **Backbone:** DeiT-Small |
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- **Token Reduction Method:** ATC |
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- **Linkage Function:** Single |
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- **Reduction Ratio:** {0.25, 0.5, 0.7, 0.9} |
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- **Reduction Stages:** 3, 6, 9 |
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### More Resources |
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- **Repository:** [https://github.com/JoakimHaurum/ATC](https://github.com/JoakimHaurum/ATC) |
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- **Paper:** [TBD](TBD) |
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- **Project Page:** [https://vap.aau.dk/atc](https://vap.aau.dk/atc) |
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- **HuggingFace Collection:** [https://huggingface.co/collections/joakimbh/agglomerative-token-clustering-66e94dfb313e85ec97590fe4](https://huggingface.co/collections/joakimbh/agglomerative-token-clustering-66e94dfb313e85ec97590fe4) |
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### Use |
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The model files contain both standard and EMA model parameters. The version which gave the best performance is indicated with the "ema_best" boolean. |
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