Transformer Encoder Layer Structure

This diagram outlines the core structure of a Transformer Encoder. The flow begins with Input Embedding, followed by Positional Encoding to capture word order. The Attention Layer then helps the model focus on relevant tokens. Add and Norm layers ensure stability, and a Feed Forward layer refines the representation. This flow is repeated multiple times in typical Transformer models to build a context-aware understanding of input text.