Attention Mechanism (5): Principles and Implementation of Transformer Architecture, Actual Machine Translation - Code World

Attention Mechanism (5): Principles and Implementation of Transformer Architecture, Actual Machine Translation

Enterprise 2023-06-21 15:02:48 views: null

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Origin blog.csdn.net/qq_51957239/article/details/129732840

Attention Mechanism (5): Principles and Implementation of Transformer Architecture, Actual Machine Translation

Essentials Attention mechanism summary attached: implementation English machine translation!

Machine translation and related technologies, and Seq2seq attention mechanism model, Transformer

Hexagonal Architecture original translation: Hexagonal Architecture: three principles and an implementation example

Implementing machine translation using RNN joint attention mechanism

Encoder structure implementation of Transformer model 1 (mask tensor + attention mechanism)

Translation: Detailed illustration of Transformer's multi-head self-attention mechanism Attention Is All You Need

Paper Translation - Machine Translation: Attention

Paper: The Origin of the Transformer Model - Google Machine Translation Team in 2017 - Translation and Interpretation of "Transformer: Attention Is All You Need" - 20230802 Edition

Decoding Transformer: Detailed description and code implementation of self-attention mechanism and codec mechanism

Study Notes -Transformer the attention mechanism

Transformer-01 Attention Mechanism

Self-attention mechanism and transformer

Attention mechanism CBAM implementation

A little exploration of Attention (attention mechanism) in Transformer

Task04: machine translation and related technology; attention mechanisms and Seq2seq model; Transformer

PyTorch uses Transformer for machine translation

Python-Tensorflow2.0 project combat-SequencetoSequence combined with attention mechanism to achieve machine translation

[Wanzi long text] In-depth analysis of Transformer and attention mechanism (including complete code implementation)

[Animation explains the principles of artificial intelligence in detail] What is the working process of the attention mechanism in the Transformer model? A detailed explanation of the mechanism example video animation of a Seq2seq model with attention

CBAM attention mechanism - pytorch implementation

BAM attention mechanism - pytorch implementation

ECANet attention mechanism - pytorch implementation

BoTNet attention mechanism - pytorch implementation

SENet attention mechanism - pytorch implementation

Nacos Architecture and Principles - Addressing Mechanism

Deeply understand the BERT Transformer, not just the attention mechanism

Attention mechanism - Spatial Transformer Networks (STN)

YOLOv5+ hybrid attention mechanism increased by another 4.3%, and the Transformer hybrid design can still roll

Demystifying Machine Learning Transformer Architecture

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