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And The Attention Mechanism: Transformers by Zakariae BAHARI is a document available to read on EtoBox.

The document discusses the Transformer model introduced in 2017 to overcome limitations of traditional architectures like RNNs and CNNs in processing sequential data, particularly in NLP tasks. It highlights the self-attention mechanism that allows Transformers to capture both short- and long-range dependencies, enabling parallel processing of sequences. Additionally, it outlines the architecture

Author
Zakariae BAHARI
Language
EN