What does the "context window" refer to in transformer models?

The term "context window" in transformer models specifically refers to the range of tokens that the model considers when processing input text. This window defines the maximum number of tokens (words or subwords) that can be processed simultaneously, allowing the model to understand context and relationships among the tokens effectively. This capacity enables the model to capture dependencies and relationships in the text which is crucial for tasks such as text generation and comprehension.

By focusing only on the relevant tokens within this specified window, transformer models can better analyze sequences and generate coherent and contextually appropriate outputs. Thus, the context window is integral to how these models interpret and generate language, as it dictates how much information the model can consider at any given time.