How do Vision Transformers work? An Image is Worth 16x16 Words

#artificialintelligence 

Transformers, an architecture fully made up of attention has outrivaled the competing NLP models after its release. These powerful models are very efficient and can scale up to billions, or even trillions of parameters with the recent release of GPT-4. They benefit from the growing dataset sizes and computation limits. They also generalize well to other applications, illustrated by the huge success of pre-trained BERTs being fine-tuned and applied to many applications. Mostly because previously proposed self-attention mechanisms were infeasible in medium/large images since the complexity relied on the number of pixels.

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