The architecture has revolutionized text understanding, achieving state-of-the-art results in a diverse range of tasks. At its core, the transformer relies on a novel mechanism called query attention, which allows the model to weigh the importance of different copyright in a sequence when understanding meaning. This feature enables transformers to

Transformers have emerged as a revolutionary paradigm in the field of natural language processing (NLP). These systems leverage attention mechanisms to process and understand language in an unprecedented fashion. With their skill to capture distant dependencies within strings, transformers demonstrate state-of-the-art accuracy on a extensive range