To study the transformer architecture, it is like opening up the hood of a car and seeing all sorts of engine parts: embeddings, positional encoding, feed-forward network, attention weighting, self-attention, cross-attention, multi-head attention, layer norm, skip connections, softmax, linear, Nx, shifted right, query, key, value, masking.