Web Reference: In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which text is converted to numerical representations called tokens, and each token is converted into a vector via lookup from a word embedding table. [1] Dec 10, 2025 · Transformer is a neural network architecture used for performing machine learning tasks particularly in natural language processing (NLP) and computer vision. In 2017 Vaswani et al. published a paper " Attention is All You Need" in which the transformers architecture was introduced. Transformers are powerful neural architectures designed primarily for sequential data, such as text. At their core, transformers are typically auto-regressive, meaning they generate sequences by predicting each token sequentially, conditioned on previously generated tokens.
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