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Transformer (deep learning)

In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which input data such as text, images, or audio, is converted to a sequence of numerical representations called tokens, and each token is converted into a vector via lookup from a word embedding table. At each layer…

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Explore the main themes, entities and connections around Transformer (deep learning). Start with the topic map, then use the sections below for research and deeper semantic analysis.

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Overview

History

Training

Architecture

Full transformer architecture

Subsequent work

Applications

Advanced semantic analysis

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Map overview Semantic statistics

Transformer (deep learning)

Nodes158
Edges157
Triples24
Avg. degree1.99
Density0.012658
Components1

How this topic connects Entity context

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Important terminology Word statistics

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Important terminology

attention displaystyle transformer text tokens token model encoder used decoder sequence vector layer output transformers input matrix mechanism one models

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
textinstance ofin which input data0.80text
imagesinstance ofin which input data0.80text
or audioinstance ofin which input data0.80text
is converted to a sequence of numerical representations called tokensinstance ofin which input data0.80text
and each token is converted into a vector via lookup from a word embedding tableinstance ofin which input data0.80text
transformerinstance ofThese classes are independent of a specific modeling architecture0.80text
but they are often discussed in the context of transformer.In a masked taskinstance ofThese classes are independent of a specific modeling architecture0.80text
one or more of the tokens is masked outinstance ofThese classes are independent of a specific modeling architecture0.80text
and the model would produce a probability distribution predicting what the masked-out tokens are based on the contextinstance ofThese classes are independent of a specific modeling architecture0.80text
TensorFlowinstance ofEfficient implementationThe transformer model has been implemented in standard deep learning frameworks0.80text
PyTorchinstance ofEfficient implementationThe transformer model has been implemented in standard deep learning frameworks0.80text
GPT-2instance ofMany large language models0.80text

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

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