A Transformer is a neural network architecture designed for handling sequences (like text), where attention replaces recurrence. Instead of reading one token at a time (like RNNs or LSTMs), Transformers process entire sequences in parallel, using self-attention to capture relationships between tokens — regardless of their distance in the sequence.
Let's break down the Transformer architecture step by step, using an intuitive approach for beginners and providing deeper mathematical insights for intermediate readers.
- Click Here - 1: Beginning to understand Transformer architecture
- Click Here - 2: Going into maths some and details