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Decoder Flow in Transformer Model

CodeEmporium via YouTube

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Overview

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This course walks through implementing a Transformer decoder from scratch, including its forward pass and core decoder-layer components such as masking, attention, normalization, dropout, and feed-forward activation.

Syllabus

Introduction
Parameters of Transformer
Inputs and Outputs of Transformer
Masking
Instantiating Decoder
Decoder Forward Pass
Decoder Layer
Masked Multi Head Self Attention
Dropout + Layer Normalization
Multi Head Cross Attention
Feed Forward, Activation
Completing the decoder flow

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