Transformer (deep learning architecture)
id:
transformer-deep-learning-architecture-208-250491
title:
Transformer (deep learning architecture)
text:
A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". Text is converted to numerical representations called tokens, and each token is converted into a vector via looking up from a word embedding table. At each layer, each token is then contextualized within the scope of the context window with other (unmasked) tokens via a parallel multi-head attention mechanism allow
brand slug:
wiki
category slug:
encyclopedia
description:
Machine learning algorithm used for natural-language processing
original url:
https://en.wikipedia.org/wiki/Transformer_(deep_learning_architecture)
date created:
2019-08-25T16:32:02Z
date modified:
2024-09-11T04:27:18Z
main entity:
{"identifier":"Q85810444","url":"https://www.wikidata.org/entity/Q85810444"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/3/34/Transformer%2C_full_architecture.png","width":1426,"height":1500}
fields total:
13
integrity:
16