SOMETHING ALONG THESE LINES:

The Transformer architecture uses attention mechanisms to process all words in a sentence simultaneously, allowing the model to understand the context and relationships between words more effectively. This parallel processing method makes it faster and more efficient than traditional sequential models, improving performance on tasks like translation and text generation. By using self-attention and positional encoding, the Transformer can accurately handle the order and significance of words in a sentence.

Viswani et al. 2017