Attention Visualization: Understanding Transformer Models | AI Knowledge Hub

Understanding What Attention Mechanisms Focus On in Transformer Models

The attention mechanism is the core of the transformer architecture, which forms the basis for modern language models such as BERT, GPT, and T5.

Visualizing attention weights allows us to understand which parts of the input a model focuses on when processing information.

Text with Highlighting Where Intensity Corresponds to Attention

Applications of Visualization

Problem Detection: Does the model attend to the right parts? Are there unexpected patterns?

Attention Can Also Be Informative.

❓ How can multi-head attention be visualized?

Answer: Each head can be shown individually or aggregated (average, maximum).

Frequently asked questions