Parametric language models are characterized by a fixed set of parameters that define the model’s architecture and capacity. In contrast, non-parametric language models possess a dynamic parameter space that expands or contracts based on the complexity of the input data. This flexibility allows non-parametric models to adapt to a wider range of linguistic contexts and variations, making them more versatile in handling diverse language tasks.
