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It uses attention mechanisms to process data in parallel
It relies on convolutional layers for image processing
It applies recurrent layers for sequence modeling
It is based on a simple feedforward neural network
Understanding the Answer
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Transformers use attention to look at all words at once. Other options are incorrect because The idea that Transformers rely on convolutional layers is a misconception; Some think Transformers use recurrent layers.
Key Concepts
Transformer Architecture
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Definition
The Transformer is a network architecture based solely on attention mechanisms, eliminating the need for recurrent or convolutional layers. It connects encoder and decoder through attention, enabling parallelization and faster training. The model has shown superior performance in machine translation tasks.
Topic Definition
The Transformer is a network architecture based solely on attention mechanisms, eliminating the need for recurrent or convolutional layers. It connects encoder and decoder through attention, enabling parallelization and faster training. The model has shown superior performance in machine translation tasks.
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