{"id":258,"date":"2024-12-23T16:23:23","date_gmt":"2024-12-23T16:23:23","guid":{"rendered":"https:\/\/aiopentext.itd.cnr.it\/spanishwithchatgpt\/?post_type=chapter&#038;p=258"},"modified":"2025-06-18T15:18:53","modified_gmt":"2025-06-18T15:18:53","slug":"transformers","status":"publish","type":"chapter","link":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/chapter\/transformers\/","title":{"raw":"Transformadores","rendered":"Transformadores"},"content":{"raw":"<p class=\"no-indent\">Los transformadores son un modelo de red neuronal dise\u00f1ado para superar las limitaciones de las redes neuronales recurrentes en el an\u00e1lisis de secuencias de datos (en nuestro caso, palabras o tokens)<sup>1<\/sup>.<\/p>\r\n<p class=\"indent\">Espec\u00edficamente, los transformadores, a trav\u00e9s del mecanismo de <em>autoatenci\u00f3n<\/em>, permiten paralelizar el an\u00e1lisis de secuencias de datos y extraer las dependencias entre los elementos de estas secuencias y los contextos en los que se producen.<\/p>\r\n\r\n\r\n<hr \/>\r\n\r\n<ol>\r\n \t<li class=\"hanging-indent\">Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, \u0141., &amp; Polosukhin, I. (2017). Attention is all you need. <em data-start=\"219\" data-end=\"274\">Advances in Neural Information Processing Systems, 30<\/em>. <a class=\"cursor-pointer\" href=\"https:\/\/papers.nips.cc\/paper_files\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf\" target=\"_new\" rel=\"noopener\" data-start=\"276\" data-end=\"369\">https:\/\/papers.nips.cc\/paper_files\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf<\/a><\/li>\r\n<\/ol>","rendered":"<p class=\"no-indent\">Los transformadores son un modelo de red neuronal dise\u00f1ado para superar las limitaciones de las redes neuronales recurrentes en el an\u00e1lisis de secuencias de datos (en nuestro caso, palabras o tokens)<sup>1<\/sup>.<\/p>\n<p class=\"indent\">Espec\u00edficamente, los transformadores, a trav\u00e9s del mecanismo de <em>autoatenci\u00f3n<\/em>, permiten paralelizar el an\u00e1lisis de secuencias de datos y extraer las dependencias entre los elementos de estas secuencias y los contextos en los que se producen.<\/p>\n<hr \/>\n<ol>\n<li class=\"hanging-indent\">Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, \u0141., &amp; Polosukhin, I. (2017). Attention is all you need. <em data-start=\"219\" data-end=\"274\">Advances in Neural Information Processing Systems, 30<\/em>. <a class=\"cursor-pointer\" href=\"https:\/\/papers.nips.cc\/paper_files\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf\" target=\"_new\" rel=\"noopener\" data-start=\"276\" data-end=\"369\">https:\/\/papers.nips.cc\/paper_files\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf<\/a><\/li>\n<\/ol>\n","protected":false},"author":3,"menu_order":15,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":224,"_links":{"self":[{"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/chapters\/258"}],"collection":[{"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/wp\/v2\/users\/3"}],"version-history":[{"count":7,"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/chapters\/258\/revisions"}],"predecessor-version":[{"id":693,"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/chapters\/258\/revisions\/693"}],"part":[{"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/parts\/224"}],"metadata":[{"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/chapters\/258\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/wp\/v2\/media?parent=258"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/pressbooks\/v2\/chapter-type?post=258"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/wp\/v2\/contributor?post=258"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/IAparaprofesores\/wp-json\/wp\/v2\/license?post=258"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}