Transformer architecture explained?

The positional encoding is crucial for understanding sequence order since there's no inherent ordering.

Self-attention enables parallel processing, which makes transformers much faster to train than RNNs.

The attention mechanism is the key innovation. It allows the model to focus on relevant parts of the input.

Multi-head attention allows the model to attend to different types of relationships simultaneously.