The framework has revolutionized natural language processing, achieving state-of-the-art results in a broad spectrum of tasks. At its core, the transformer relies on a novel mechanism called intra-attention, which allows the model to weigh the significance of different copyright in a text passage when comprehending meaning. This feature enables tra

Transformers have emerged as a powerful paradigm in the field of natural language processing (NLP). These systems leverage attention mechanisms to process and understand text in an unprecedented manner. With their capability to capture distant dependencies within strings, transformers exhibit state-of-the-art performance on a broad range of NLP tas