Transformer functionality refers to the mechanism by which transformer models process and generate data, utilizing self-attention mechanisms to weigh the importance of different input tokens dynamically. This architecture enables efficient parallel processing and has revolutionized natural language processing tasks by allowing models to understand context and relationships in data more effectively.