Transformer blocks

Transformer blocks refer to the fundamental building blocks of the Transformer architecture, which is a neural network architecture used in natural language processing tasks such as language modeling and machine translation. A Transformer block contains a self-attention layer and a feed-forward neural network layer, which work together to learn contextualized representations of words or subwords in a sequence. Multiple Transformer blocks can be stacked on top of each other to form a deep neural network, which is capable of learning sophisticated language patterns and relationships.