Top books on Transformers in 2022

In 2017, the Google Brain team introduced Transformers in a paper called, Attention is all you need. They proposed a new simple network architecture based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Today, transformers have become the model of choice for NLP and computer vision. The Transformer architecture implements an encoder-decoder structure without recurrence and convolutions. Taking cognizance of the importance of Transformers in machine learning and AI, we have listed five books to understand the sequence transduction model better.