Transformer Architecture

A neural network architecture that relies heavily on self-attention mechanisms to weigh the importance of different parts of the input data. This allows it to process sequences, like text or time series, in parallel rather than sequentially, leading to efficient training and powerful performance in tasks such as language translation and text generation.