{"id":243,"date":"2023-11-22T13:38:45","date_gmt":"2023-11-22T13:38:45","guid":{"rendered":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/chapter\/transformers\/"},"modified":"2024-01-31T08:12:21","modified_gmt":"2024-01-31T08:12:21","slug":"transformers","status":"publish","type":"chapter","link":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/chapter\/transformers\/","title":{"raw":"Transformers","rendered":"Transformers"},"content":{"raw":"<p class=\"no-indent\">Transformers are a neural network model designed to overcome the limitations of recurrent neural networks in the analysis of sequences of data (in our case, words or tokens)<sup>1<\/sup>.<\/p>\n<p class=\"indent\">Specifically, transformers, through the <em>self-attention<\/em> mechanism, make it possible to parallelise the analysis of data sequences and extract the dependencies between the elements of these sequences and the contexts in which they occur.<\/p>\n&nbsp;\n\n<hr>\n<p class=\"hanging-indent\" style=\"text-align: left\"><sup>1\u00a0<\/sup>Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... &amp; Polosukhin, I., <em>Attention is all you need<\/em>, Advances in neural information processing systems, 30, 2017.<\/p>","rendered":"<p class=\"no-indent\">Transformers are a neural network model designed to overcome the limitations of recurrent neural networks in the analysis of sequences of data (in our case, words or tokens)<sup>1<\/sup>.<\/p>\n<p class=\"indent\">Specifically, transformers, through the <em>self-attention<\/em> mechanism, make it possible to parallelise the analysis of data sequences and extract the dependencies between the elements of these sequences and the contexts in which they occur.<\/p>\n<p>&nbsp;<\/p>\n<hr \/>\n<p class=\"hanging-indent\" style=\"text-align: left\"><sup>1\u00a0<\/sup>Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., &#8230; &amp; Polosukhin, I., <em>Attention is all you need<\/em>, Advances in neural information processing systems, 30, 2017.<\/p>\n","protected":false},"author":1,"menu_order":16,"template":"","meta":{"pb_show_title":"","pb_short_title":"","pb_subtitle":"","pb_authors":["manuel-gentile","fabrizio-falchi"],"pb_section_license":""},"chapter-type":[49],"contributor":[71,63],"license":[],"part":204,"_links":{"self":[{"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/chapters\/243"}],"collection":[{"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":1,"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/chapters\/243\/revisions"}],"predecessor-version":[{"id":244,"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/chapters\/243\/revisions\/244"}],"part":[{"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/parts\/204"}],"metadata":[{"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/chapters\/243\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/wp\/v2\/media?parent=243"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/pressbooks\/v2\/chapter-type?post=243"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/wp\/v2\/contributor?post=243"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/aiopentext.itd.cnr.it\/aiforteacher\/wp-json\/wp\/v2\/license?post=243"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}