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The use of self-attention mechanisms allows for better context understanding.
It is based solely on recurrent neural networks.
It requires less data for training than traditional models.
It eliminates the need for any form of neural networks.
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The Transformer uses a self‑attention mechanism. Other options are incorrect because Some think Transformers use only recurrent neural networks (RNNs); It is often said Transformers need less data.
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Contributors to Transformer Model
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Deep Dive: Contributors to Transformer Model
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Definition
Several individuals have made significant contributions to the development of the Transformer model. Each contributor played a unique role in designing, implementing, and improving different aspects of the model, leading to its success in machine translation tasks.
Topic Definition
Several individuals have made significant contributions to the development of the Transformer model. Each contributor played a unique role in designing, implementing, and improving different aspects of the model, leading to its success in machine translation tasks.
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