import{s as X,n as I,o as J}from"../chunks/scheduler.37c15a92.js";import{S as K,i as V,g as r,s as o,r as D,A as W,h as i,f as n,c as a,j as O,u as G,x,k as Q,y as Z,a as s,v as R,d as S,t as j,w as k}from"../chunks/index.2bf4358c.js";import{Y as ee}from"../chunks/Youtube.1e50a667.js";import{C as te}from"../chunks/CourseFloatingBanner.15ba07e6.js";import{H as ne,E as se}from"../chunks/EditOnGithub.8916dc7c.js";function oe(q){let l,w,_,C,m,b,f,T,p,P,u,U="Decoder models use only the decoder of a Transformer model. At each stage, for a given word the attention layers can only access the words positioned before it in the sentence. These models are often called <em>auto-regressive models</em>.",y,c,Y="The pretraining of decoder models usually revolves around predicting the next word in the sentence.",L,d,B="These models are best suited for tasks involving text generation.",E,h,F="Representatives of this family of models include:",H,$,N='<li><a href="https://huggingface.co/transformers/model_doc/ctrl" rel="nofollow">CTRL</a></li> <li><a href="https://huggingface.co/docs/transformers/model_doc/openai-gpt" rel="nofollow">GPT</a></li> <li><a href="https://huggingface.co/transformers/model_doc/gpt2" rel="nofollow">GPT-2</a></li> <li><a href="https://huggingface.co/transformers/model_doc/transfo-xl" rel="nofollow">Transformer XL</a></li>',M,g,z,v,A;return m=new ne({props:{title:"Decoder models",local:"decoder-models",headingTag:"h1"}}),f=new te({props:{chapter:1,classNames:"absolute z-10 right-0 top-0"}}),p=new ee({props:{id:"d_ixlCubqQw"}}),g=new se({props:{source:"https://github.com/huggingface/course/blob/main/chapters/en/chapter1/6.mdx"}}),{c(){l=r("meta"),w=o(),_=r("p"),C=o(),D(m.$$.fragment),b=o(),D(f.$$.fragment),T=o(),D(p.$$.fragment),P=o(),u=r("p"),u.innerHTML=U,y=o(),c=r("p"),c.textContent=Y,L=o(),d=r("p"),d.textContent=B,E=o(),h=r("p"),h.textContent=F,H=o(),$=r("ul"),$.innerHTML=N,M=o(),D(g.$$.fragment),z=o(),v=r("p"),this.h()},l(e){const t=W("svelte-u9bgzb",document.head);l=i(t,"META",{name:!0,content:!0}),t.forEach(n),w=a(e),_=i(e,"P",{}),O(_).forEach(n),C=a(e),G(m.$$.fragment,e),b=a(e),G(f.$$.fragment,e),T=a(e),G(p.$$.fragment,e),P=a(e),u=i(e,"P",{"data-svelte-h":!0}),x(u)!=="svelte-1n9iaa3"&&(u.innerHTML=U),y=a(e),c=i(e,"P",{"data-svelte-h":!0}),x(c)!=="svelte-5nsp9x"&&(c.textContent=Y),L=a(e),d=i(e,"P",{"data-svelte-h":!0}),x(d)!=="svelte-zgz7vj"&&(d.textContent=B),E=a(e),h=i(e,"P",{"data-svelte-h":!0}),x(h)!=="svelte-s27rrg"&&(h.textContent=F),H=a(e),$=i(e,"UL",{"data-svelte-h":!0}),x($)!=="svelte-1p88rih"&&($.innerHTML=N),M=a(e),G(g.$$.fragment,e),z=a(e),v=i(e,"P",{}),O(v).forEach(n),this.h()},h(){Q(l,"name","hf:doc:metadata"),Q(l,"content",ae)},m(e,t){Z(document.head,l),s(e,w,t),s(e,_,t),s(e,C,t),R(m,e,t),s(e,b,t),R(f,e,t),s(e,T,t),R(p,e,t),s(e,P,t),s(e,u,t),s(e,y,t),s(e,c,t),s(e,L,t),s(e,d,t),s(e,E,t),s(e,h,t),s(e,H,t),s(e,$,t),s(e,M,t),R(g,e,t),s(e,z,t),s(e,v,t),A=!0},p:I,i(e){A||(S(m.$$.fragment,e),S(f.$$.fragment,e),S(p.$$.fragment,e),S(g.$$.fragment,e),A=!0)},o(e){j(m.$$.fragment,e),j(f.$$.fragment,e),j(p.$$.fragment,e),j(g.$$.fragment,e),A=!1},d(e){e&&(n(w),n(_),n(C),n(b),n(T),n(P),n(u),n(y),n(c),n(L),n(d),n(E),n(h),n(H),n($),n(M),n(z),n(v)),n(l),k(m,e),k(f,e),k(p,e),k(g,e)}}}const ae='{"title":"Decoder models","local":"decoder-models","sections":[],"depth":1}';function le(q){return J(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class ue extends K{constructor(l){super(),V(this,l,le,oe,X,{})}}export{ue as component};
