The 2017 research paper introducing the Transformer architecture describes sequence modelling based on attention rather than recurrent or convolutional networks. Its machine-translation experiments make it a foundational source for understanding a major shift in modern AI. Best suited to machine-learning students and practitioners who want to read the original technical argument, with the mathematical detail expected of a research paper.