DeBERTa is a model that incorporates disentangled attention and an enhanced mask decoder to improve language models. Disentangled attention helps capture content-to-position relations, while the enhanced mask decoder incorporates absolute positioning. These techniques have shown improvements in NLP benchmarks and have made DeBERTa a popular choice in NLP pipelines.
