Transformers as the name implies are used to transform objects. Therefore, to see if performance improvements carried over to even larger scales, we trained a 600M-parameter ViT model. Our data suggest that (1) with sufficient training ViT can perform very well, and (2) ViT yields an excellent performance/compute trade-off at both smaller and larger compute scales. High-Performing Large-Scale Image Recognition.Instead it was called Attention is All You Need.
In fact, the title of the 2017 paper that introduced Transformers wasn’t called, We Present You the Transformer. Got that? Attention is a neural network structure that you’ll hear about all over the place in machine learning these days. THE NEXT IMPORTANT PART OF TRANSFORMERS IS CALLED ATTENTION.Learn more about Transformers → more about AI → out IBM Watson →.
