Transformer Neural Network is a type of neural network architecture predominantly used in the field of natural language processing (NLP). Introduced in the paper "Attention Is All You Need", transformers have been influential in advancing the state of the art in NLP tasks.
How Transformer Neural Networks Work
Transformers use a mechanism called 'attention' to weigh the significance of different parts of the input data. Unlike previous architectures, they do not rely on sequential data processing, which allows for more parallelization and faster training. They are particularly effective in handling long-range dependencies in text.
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