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README.md
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_By [Aritra Roy Gosthipaty](https://github.com/ariG23498) and [Sayak Paul](https://github.com/sayakpaul) (equal contribution)_
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<br>
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<hr>
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We probe into the representations learned by different families of Vision Transformers (supervised pre-training with ImageNet-21k, ImageNet-1k, distillation, self-supervised pre-training):
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<ul>
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<li> Original ViT [1] </li>
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<li> DeiT [2] </li>
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<li> DINO [3] </li>
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</ul>
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We hope these tools will prove to be useful for the community. Please follow along with [this post on keras.io](https://keras.io/examples/vision/probing_vits/) for a better navigation through the repository.
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<hr>
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References
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<ol>
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<li> [1] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929 </li>
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<li> [2] DeiT: https://arxiv.org/abs/2012.12877 </li>
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<li> [3] DINO: https://arxiv.org/abs/2104.14294 </li>
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</ol>
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<br>
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<hr>
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<br>
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Acknowledgements
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<ul>
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<li> <a href="https://pyimagesearch.com">PyImageSearch</a> </li>
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<li> <a href="https://jarvislabs.ai/">Jarvislabs.ai</a> </li>
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<li> <a href="https://developers.google.com/programs/experts/">GDE Program</a> </li>
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</ul>
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