In many of the cases, we see that the traditional neural networks are not capable of holding and working on long and large information. attention layer can help a neural
Amazon introduced a transformer-based cross-modal recipe retrieval method that is straightforward, simple and versatile to train and deploy
T2T-ViT employs progressive tokenization that takes patches of an image and converts it into an overlapped-token over a few iterations
Evolved Transformer has been evolved with neural architecture search (NAS) to perform sequence-to-sequence tasks such as neural machine translation (NMT)
Self-Attention Computer Vision is a PyTorch based library providing a one-stop solution for all of the self-attention based requirements
Transformer XL is a Transformer model that allows us to model long range dependencies while not disrupting the temporal coherence.
Our brain is modular by design and is characterised by distinct but interacting subsystems which handle important functions like memory, language and perception. Attention is studied in neuroscience as an
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