Learning Path
Question & Answer
Choose the Best Answer
Input Embedding → Attention Mechanism → Output Decoding → Final Output
Attention Mechanism → Input Embedding → Final Output → Output Decoding
Input Embedding → Output Decoding → Attention Mechanism → Final Output
Output Decoding → Attention Mechanism → Input Embedding → Final Output
Understanding the Answer
Let's break down why this is correct
First the words are turned into numbers that the computer can read. Other options are incorrect because It starts by looking at relationships before the words are even turned into numbers, which is impossible; It says decoding happens before attention, but attention must happen first to know which words matter.
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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