# OnCo record transformer-architecture (term). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)". Whole corpus: https://onco.cc/api/v1/onco.nt
@prefix schema: <https://schema.org/> .
@prefix onco: <https://onco.cc/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://onco.cc/terms/transformer-architecture/>
  a schema:DefinedTerm ;
  onco:kind "term" ;
  schema:identifier "transformer-architecture" ;
  schema:name "Transformer and attention"@en ;
  schema:alternateName "transformer architecture"@en, "transformer model"@en, "transformer encoder"@en, "attention mechanism"@en, "self-attention"@en, "multi-head attention"@en, "attention weights"@en, "fusion transformer"@en, "Perceiver"@en ;
  schema:description "A transformer is a neural network that turns its input into a sequence of tokens and lets every token weigh every other through attention, the architecture behind language models and most new biology models."@en ;
  schema:url <https://onco.cc/terms/transformer-architecture/> ;
  schema:dateModified "2026-09-24"^^xsd:date ;
  schema:sameAs <https://en.wikipedia.org/wiki/Transformer_(deep_learning)> ;
  schema:citation <https://en.wikipedia.org/wiki/Attention_(machine_learning)>, <https://en.wikipedia.org/wiki/Perceiver>, <https://en.wikipedia.org/wiki/Transformer_(deep_learning)> ;
  onco:tag "cansim-terms" ;
  onco:related <https://onco.cc/terms/cancer-ai-vocabulary/> ;
  onco:terms <https://onco.cc/terms/tokenisation/>, <https://onco.cc/terms/embedding/>, <https://onco.cc/terms/abmil/>, <https://onco.cc/terms/foundation-model/> .