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Question & Answer
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It uses attention mechanisms exclusively
It relies heavily on recurrent layers
It processes data in a strictly sequential manner
It requires convolutional layers for feature extraction
Understanding the Answer
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The Transformer uses only attention mechanisms. Other options are incorrect because Many think Transformers need recurrent layers; Some believe Transformers process data sequentially.
Key Concepts
Transformer Architecture
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Deep Dive: 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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