transformer-in-transformer
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Classify images using a model that focuses on both individual pixels and larger sections of the image.
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Free · no card · unsubscribe anytimeImplementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
transformer-in-transformer has 306 stars on GitHub. It has been forked 41 times. transformer-in-transformer is written mainly in Python. It has been in active development since 2021. transformer-in-transformer is available under the MIT license. Its main topics are artificial-intelligence, deep-learning, image-classification, transformers.
What is transformer-in-transformer?
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Is transformer-in-transformer open source?
transformer-in-transformer is an open-source project. It is released under the MIT license.
Is transformer-in-transformer free?
Yes. transformer-in-transformer is free and open source — you can use, modify and self-host it.
What license does transformer-in-transformer use?
transformer-in-transformer is available under the MIT license.
What language is transformer-in-transformer written in?
transformer-in-transformer is written mainly in Python.
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