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Transformer Architecture
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In the Transformer architecture, the primary mechanism that connects the encoder and decoder is called ____. This mechanism allows for parallelization and has improved the efficiency of training models compared to traditional methods.

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Learning Path
Learning Path

Question & Answer
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2
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3
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Choose AnswerChoose the Best Answer

A

Attention

B

Convolution

C

Recurrent Neural Networks

D

Pooling

Understanding the Answer

Let's break down why this is correct

Attention lets the model look at all parts of the input at once. Other options are incorrect because Convolution is a sliding‑window filter used in image nets; RNNs read words one after another.

Key Concepts

Attention Mechanism
Neural Network Architectures
Parallelization in Training
Topic

Transformer Architecture

Difficulty

medium level question

Cognitive Level

understand

Deep Dive: Transformer Architecture

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Definition
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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