Create README.md

README.md

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