course/pr_1159/ro/_app/immutable/nodes/9.7961ba7b.js

import{s as J,n as K,o as V}from"../chunks/scheduler.893fe8c9.js";import{S as W,i as Z,e as o,s as l,c as C,h as ee,a as s,d as n,b as r,f as X,g as b,j as w,k as I,l as te,m as a,n as P,t as z,o as T,p as y}from"../chunks/index.6ee278c6.js";import{C as ne,H as ae,E as le}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.bf8908ef.js";import{Y as re}from"../chunks/Youtube.59d04f41.js";import{C as ie}from"../chunks/CourseFloatingBanner.b902b8d5.js";function oe(k){let i,M,x,L,m,E,p,H,f,S,u,A,c,B="Modelele Decoder utilizează doar decoder-ul unui model Transformer. În fiecare etapă, pentru un cuvânt dat, layerele de atenție pot accesa doar cuvintele poziționate înaintea acestuia în propoziție. Aceste modele sunt adesea numite <em>modele autoregresive</em>.",D,d,F="Preantrenarea modelelor de decodare se axează de obicei pe prezicerea următorului cuvânt din propoziție.",G,$,N="Aceste modele sunt cele mai potrivite pentru sarcinile care implică generarea de text.",j,g,O="Printre reprezentanții acestei familii de modele se numără:",q,_,Q='<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>',R,h,U,v,Y;return m=new ne({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),p=new ae({props:{title:"Modele Decoder",local:"modele-decoder",headingTag:"h1"}}),f=new ie({props:{chapter:1,classNames:"absolute z-10 right-0 top-0"}}),u=new re({props:{id:"d_ixlCubqQw"}}),h=new le({props:{source:"https://github.com/huggingface/course/blob/main/chapters/ro/chapter1/6.mdx"}}),{c(){i=o("meta"),M=l(),x=o("p"),L=l(),C(m.$$.fragment),E=l(),C(p.$$.fragment),H=l(),C(f.$$.fragment),S=l(),C(u.$$.fragment),A=l(),c=o("p"),c.innerHTML=B,D=l(),d=o("p"),d.textContent=F,G=l(),$=o("p"),$.textContent=N,j=l(),g=o("p"),g.textContent=O,q=l(),_=o("ul"),_.innerHTML=Q,R=l(),C(h.$$.fragment),U=l(),v=o("p"),this.h()},l(e){const t=ee("svelte-u9bgzb",document.head);i=s(t,"META",{name:!0,content:!0}),t.forEach(n),M=r(e),x=s(e,"P",{}),X(x).forEach(n),L=r(e),b(m.$$.fragment,e),E=r(e),b(p.$$.fragment,e),H=r(e),b(f.$$.fragment,e),S=r(e),b(u.$$.fragment,e),A=r(e),c=s(e,"P",{"data-svelte-h":!0}),w(c)!=="svelte-52g9yp"&&(c.innerHTML=B),D=r(e),d=s(e,"P",{"data-svelte-h":!0}),w(d)!=="svelte-1ljizve"&&(d.textContent=F),G=r(e),$=s(e,"P",{"data-svelte-h":!0}),w($)!=="svelte-1pcty4z"&&($.textContent=N),j=r(e),g=s(e,"P",{"data-svelte-h":!0}),w(g)!=="svelte-dd7odx"&&(g.textContent=O),q=r(e),_=s(e,"UL",{"data-svelte-h":!0}),w(_)!=="svelte-1p88rih"&&(_.innerHTML=Q),R=r(e),b(h.$$.fragment,e),U=r(e),v=s(e,"P",{}),X(v).forEach(n),this.h()},h(){I(i,"name","hf:doc:metadata"),I(i,"content",se)},m(e,t){te(document.head,i),a(e,M,t),a(e,x,t),a(e,L,t),P(m,e,t),a(e,E,t),P(p,e,t),a(e,H,t),P(f,e,t),a(e,S,t),P(u,e,t),a(e,A,t),a(e,c,t),a(e,D,t),a(e,d,t),a(e,G,t),a(e,$,t),a(e,j,t),a(e,g,t),a(e,q,t),a(e,_,t),a(e,R,t),P(h,e,t),a(e,U,t),a(e,v,t),Y=!0},p:K,i(e){Y||(z(m.$$.fragment,e),z(p.$$.fragment,e),z(f.$$.fragment,e),z(u.$$.fragment,e),z(h.$$.fragment,e),Y=!0)},o(e){T(m.$$.fragment,e),T(p.$$.fragment,e),T(f.$$.fragment,e),T(u.$$.fragment,e),T(h.$$.fragment,e),Y=!1},d(e){e&&(n(M),n(x),n(L),n(E),n(H),n(S),n(A),n(c),n(D),n(d),n(G),n($),n(j),n(g),n(q),n(_),n(R),n(U),n(v)),n(i),y(m,e),y(p,e),y(f,e),y(u,e),y(h,e)}}}const se='{"title":"Modele Decoder","local":"modele-decoder","sections":[],"depth":1}';function me(k){return V(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class $e extends W{constructor(i){super(),Z(this,i,me,oe,J,{})}}export{$e as component};