import{s as Q,n as X,o as I}from"../chunks/scheduler.37c15a92.js";import{S as J,i as K,g as r,s as a,r as k,A as O,h as m,f as l,c as s,j as F,u as q,x,k as N,y as V,a as n,v as S,d as j,t as z,w as A}from"../chunks/index.2bf4358c.js";import{Y as W}from"../chunks/Youtube.1e50a667.js";import{C as Z}from"../chunks/CourseFloatingBanner.06521e8b.js";import{H as tt}from"../chunks/Heading.8ada512a.js";function et(G){let o,v,d,C,i,w,f,P,p,T,u,R="디코더 모델(Decoder models)은 트랜스포머 모델의 디코더만 사용합니다. 각각의 단계마다, 어텐션 레이어는 주어진 단어에 대해 문장 내에서 해당 단어 앞에 위치한 단어들에 대해서만 액세스 할 수 있습니다. 이러한 모델을 <em>자동 회귀(auto-regressive) 모델</em>이라고 부릅니다.",b,c,U="디코더 모델의 사전 학습은 보통 문장 내 다음 단어 예측을 반복하는 방식으로 이루어집니다.",L,_,Y="이러한 모델은 텍스트 생성에 특화되어 있습니다.",H,$,B="디코더 모델 계열의 대표 주자들은 다음과 같습니다:",M,h,D='<li><a href="https://huggingface.co/transformers/model_doc/ctrl.html" 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.html" rel="nofollow">GPT-2</a></li> <li><a href="https://huggingface.co/transformers/model_doc/transformerxl.html" rel="nofollow">Transformer XL</a></li>',y,g,E;return i=new tt({props:{title:"디코더 모델",local:"디코더-모델",headingTag:"h1"}}),f=new Z({props:{chapter:1,classNames:"absolute z-10 right-0 top-0"}}),p=new W({props:{id:"d_ixlCubqQw"}}),{c(){o=r("meta"),v=a(),d=r("p"),C=a(),k(i.$$.fragment),w=a(),k(f.$$.fragment),P=a(),k(p.$$.fragment),T=a(),u=r("p"),u.innerHTML=R,b=a(),c=r("p"),c.textContent=U,L=a(),_=r("p"),_.textContent=Y,H=a(),$=r("p"),$.textContent=B,M=a(),h=r("ul"),h.innerHTML=D,y=a(),g=r("p"),this.h()},l(t){const e=O("svelte-u9bgzb",document.head);o=m(e,"META",{name:!0,content:!0}),e.forEach(l),v=s(t),d=m(t,"P",{}),F(d).forEach(l),C=s(t),q(i.$$.fragment,t),w=s(t),q(f.$$.fragment,t),P=s(t),q(p.$$.fragment,t),T=s(t),u=m(t,"P",{"data-svelte-h":!0}),x(u)!=="svelte-1p9xm7k"&&(u.innerHTML=R),b=s(t),c=m(t,"P",{"data-svelte-h":!0}),x(c)!=="svelte-vpsok7"&&(c.textContent=U),L=s(t),_=m(t,"P",{"data-svelte-h":!0}),x(_)!=="svelte-2694ur"&&(_.textContent=Y),H=s(t),$=m(t,"P",{"data-svelte-h":!0}),x($)!=="svelte-ov0q2c"&&($.textContent=B),M=s(t),h=m(t,"UL",{"data-svelte-h":!0}),x(h)!=="svelte-jabf5n"&&(h.innerHTML=D),y=s(t),g=m(t,"P",{}),F(g).forEach(l),this.h()},h(){N(o,"name","hf:doc:metadata"),N(o,"content",lt)},m(t,e){V(document.head,o),n(t,v,e),n(t,d,e),n(t,C,e),S(i,t,e),n(t,w,e),S(f,t,e),n(t,P,e),S(p,t,e),n(t,T,e),n(t,u,e),n(t,b,e),n(t,c,e),n(t,L,e),n(t,_,e),n(t,H,e),n(t,$,e),n(t,M,e),n(t,h,e),n(t,y,e),n(t,g,e),E=!0},p:X,i(t){E||(j(i.$$.fragment,t),j(f.$$.fragment,t),j(p.$$.fragment,t),E=!0)},o(t){z(i.$$.fragment,t),z(f.$$.fragment,t),z(p.$$.fragment,t),E=!1},d(t){t&&(l(v),l(d),l(C),l(w),l(P),l(T),l(u),l(b),l(c),l(L),l(_),l(H),l($),l(M),l(h),l(y),l(g)),l(o),A(i,t),A(f,t),A(p,t)}}}const lt='{"title":"디코더 모델","local":"디코더-모델","sections":[],"depth":1}';function nt(G){return I(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class it extends J{constructor(o){super(),K(this,o,nt,et,Q,{})}}export{it as component};
