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Blowing Up Transformer Decoder Architecture

CodeEmporium via YouTube

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Overview

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This course explains how a Transformer decoder works, covering text processing, batching, positional encoding, attention mechanisms, residual connections, and the training and inference process.

Syllabus

Introduction
What is the Encoder doing?
Text Processing
Why are we batching data?
Position Encoding
Query, Key and Value Tensors
Masked Multi Head Self Attention
Residual Connections
Multi Head Cross Attention
Finishing up the Decoder Layer
Training the Transformer
Inference for the Transformer

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CodeEmporium

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