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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 an attention mechanism that lets every word look at all others at the same time. Other options are incorrect because Some think Transformers rely on convolutional layers like those used for image recognition; A common misconception is that Transformers still use recurrent layers to remember past words.
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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