import{s as D,n as I,o as J}from"../chunks/scheduler.37c15a92.js";import{S as K,i as V,g as r,s as l,r as z,A as W,h as m,f as n,c as s,j as Q,u as G,x as C,k as X,y as Z,a,v as S,d as A,t as N,w as R}from"../chunks/index.2bf4358c.js";import{Y as tt}from"../chunks/Youtube.1e50a667.js";import{C as et}from"../chunks/CourseFloatingBanner.06521e8b.js";import{H as nt,E as at}from"../chunks/EditOnGithub.8916dc7c.js";function lt(U){let o,v,d,w,i,b,f,P,p,T,u,Y="“解码器”模型仅使用 Transformer 模型的解码器部分。在每个阶段，对于给定的单词，注意力层只能获取到句子中位于将要预测单词前面的单词。这些模型通常被称为自回归模型。",y,c,k="“解码器”模型的预训练通常围绕预测句子中的下一个单词进行。",E,$,B="这些模型最适合处理文本生成的任务。",L,h,F="该系列模型的典型代表有：",q,_,O='<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/transfor-xl" rel="nofollow">Transformer XL</a></li>',H,g,M,x,j;return i=new nt({props:{title:"“解码器”模型",local:"“解码器”模型",headingTag:"h1"}}),f=new et({props:{chapter:1,classNames:"absolute z-10 right-0 top-0"}}),p=new tt({props:{id:"d_ixlCubqQw"}}),g=new at({props:{source:"https://github.com/huggingface/course/blob/main/chapters/zh-CN/chapter1/6.mdx"}}),{c(){o=r("meta"),v=l(),d=r("p"),w=l(),z(i.$$.fragment),b=l(),z(f.$$.fragment),P=l(),z(p.$$.fragment),T=l(),u=r("p"),u.textContent=Y,y=l(),c=r("p"),c.textContent=k,E=l(),$=r("p"),$.textContent=B,L=l(),h=r("p"),h.textContent=F,q=l(),_=r("ul"),_.innerHTML=O,H=l(),z(g.$$.fragment),M=l(),x=r("p"),this.h()},l(t){const e=W("svelte-u9bgzb",document.head);o=m(e,"META",{name:!0,content:!0}),e.forEach(n),v=s(t),d=m(t,"P",{}),Q(d).forEach(n),w=s(t),G(i.$$.fragment,t),b=s(t),G(f.$$.fragment,t),P=s(t),G(p.$$.fragment,t),T=s(t),u=m(t,"P",{"data-svelte-h":!0}),C(u)!=="svelte-12adqdf"&&(u.textContent=Y),y=s(t),c=m(t,"P",{"data-svelte-h":!0}),C(c)!=="svelte-j9j86b"&&(c.textContent=k),E=s(t),$=m(t,"P",{"data-svelte-h":!0}),C($)!=="svelte-8p8dxa"&&($.textContent=B),L=s(t),h=m(t,"P",{"data-svelte-h":!0}),C(h)!=="svelte-rgo3yq"&&(h.textContent=F),q=s(t),_=m(t,"UL",{"data-svelte-h":!0}),C(_)!=="svelte-nnfpm1"&&(_.innerHTML=O),H=s(t),G(g.$$.fragment,t),M=s(t),x=m(t,"P",{}),Q(x).forEach(n),this.h()},h(){X(o,"name","hf:doc:metadata"),X(o,"content",st)},m(t,e){Z(document.head,o),a(t,v,e),a(t,d,e),a(t,w,e),S(i,t,e),a(t,b,e),S(f,t,e),a(t,P,e),S(p,t,e),a(t,T,e),a(t,u,e),a(t,y,e),a(t,c,e),a(t,E,e),a(t,$,e),a(t,L,e),a(t,h,e),a(t,q,e),a(t,_,e),a(t,H,e),S(g,t,e),a(t,M,e),a(t,x,e),j=!0},p:I,i(t){j||(A(i.$$.fragment,t),A(f.$$.fragment,t),A(p.$$.fragment,t),A(g.$$.fragment,t),j=!0)},o(t){N(i.$$.fragment,t),N(f.$$.fragment,t),N(p.$$.fragment,t),N(g.$$.fragment,t),j=!1},d(t){t&&(n(v),n(d),n(w),n(b),n(P),n(T),n(u),n(y),n(c),n(E),n($),n(L),n(h),n(q),n(_),n(H),n(M),n(x)),n(o),R(i,t),R(f,t),R(p,t),R(g,t)}}}const st='{"title":"“解码器”模型","local":"“解码器”模型","sections":[],"depth":1}';function ot(U){return J(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class ut extends K{constructor(o){super(),V(this,o,ot,lt,D,{})}}export{ut as component};
