Transformer (machine learning model)

Topic | v1 | created by janarez |

A transformer is a deep learning model that adopts the mechanism of attention, differentially weighing the significance of each part of the input data. It is used primarily in the field of natural language processing (NLP) and in computer vision (CV). Like recurrent neural networks (RNNs), transformers are designed to handle sequential input data, such as natural language, for tasks such as translation and text summarization. However, unlike RNNs, transformers do not necessarily process the data in order. Rather, the attention mechanism provides context for any position in the input sequence.


tool for Deep learning

Deep learning (also known as deep structured learning) is part of a broader family of machine learnin...

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discussed in The Annotated Transformer

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The Transformer from “Attention is All You Need” has been on a lot of people’s minds over the last ye...