The transformer model has become one of the main highlights of advances in deep learning and deep neural networks.

This is the same model OpenAI uses for prediction, summarization, question answering, and more. This article explores the architecture of Transformer models and how they work.

How this novel neural network architecture changes the way we analyze complex data types, and powers revolutionary models like GPT-3 and BERT.

The approach makes the model suitable for enterprise-scale machine translation, text summarization, computer vision and audio processing tasks as well as tasks like estimation and forecasting, TII ...

“We believe Reformer gives the basis for future use of Transformer models, both for long text and applications outside of natural language processing,” added Kaiser and Kitaev.