import{s as X,n as I,o as J}from"../chunks/scheduler.37c15a92.js";import{S as K,i as V,g as i,s as r,r as D,A as W,h as s,f as a,c as l,j as O,u as G,x as v,k as Q,y as Z,a as n,v as S,d as j,t as q,w as R}from"../chunks/index.2bf4358c.js";import{Y as ee}from"../chunks/Youtube.1e50a667.js";import{C as te}from"../chunks/CourseFloatingBanner.6add7356.js";import{H as ae,E as ne}from"../chunks/getInferenceSnippets.24b50994.js";function re(U){let o,C,_,w,m,P,p,b,u,z,f,Y="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>.",T,c,k="Preantrenarea modelelor de decodare se axează de obicei pe prezicerea următorului cuvânt din propoziție.",M,d,B="Aceste modele sunt cele mai potrivite pentru sarcinile care implică generarea de text.",y,$,F="Printre reprezentanții acestei familii de modele se numără:",L,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>',E,g,H,x,A;return m=new ae({props:{title:"Modele Decoder",local:"modele-decoder",headingTag:"h1"}}),p=new te({props:{chapter:1,classNames:"absolute z-10 right-0 top-0"}}),u=new ee({props:{id:"d_ixlCubqQw"}}),g=new ne({props:{source:"https://github.com/huggingface/course/blob/main/chapters/rum/chapter1/6.mdx"}}),{c(){o=i("meta"),C=r(),_=i("p"),w=r(),D(m.$$.fragment),P=r(),D(p.$$.fragment),b=r(),D(u.$$.fragment),z=r(),f=i("p"),f.innerHTML=Y,T=r(),c=i("p"),c.textContent=k,M=r(),d=i("p"),d.textContent=B,y=r(),$=i("p"),$.textContent=F,L=r(),h=i("ul"),h.innerHTML=N,E=r(),D(g.$$.fragment),H=r(),x=i("p"),this.h()},l(e){const t=W("svelte-u9bgzb",document.head);o=s(t,"META",{name:!0,content:!0}),t.forEach(a),C=l(e),_=s(e,"P",{}),O(_).forEach(a),w=l(e),G(m.$$.fragment,e),P=l(e),G(p.$$.fragment,e),b=l(e),G(u.$$.fragment,e),z=l(e),f=s(e,"P",{"data-svelte-h":!0}),v(f)!=="svelte-52g9yp"&&(f.innerHTML=Y),T=l(e),c=s(e,"P",{"data-svelte-h":!0}),v(c)!=="svelte-1ljizve"&&(c.textContent=k),M=l(e),d=s(e,"P",{"data-svelte-h":!0}),v(d)!=="svelte-1pcty4z"&&(d.textContent=B),y=l(e),$=s(e,"P",{"data-svelte-h":!0}),v($)!=="svelte-dd7odx"&&($.textContent=F),L=l(e),h=s(e,"UL",{"data-svelte-h":!0}),v(h)!=="svelte-1p88rih"&&(h.innerHTML=N),E=l(e),G(g.$$.fragment,e),H=l(e),x=s(e,"P",{}),O(x).forEach(a),this.h()},h(){Q(o,"name","hf:doc:metadata"),Q(o,"content",le)},m(e,t){Z(document.head,o),n(e,C,t),n(e,_,t),n(e,w,t),S(m,e,t),n(e,P,t),S(p,e,t),n(e,b,t),S(u,e,t),n(e,z,t),n(e,f,t),n(e,T,t),n(e,c,t),n(e,M,t),n(e,d,t),n(e,y,t),n(e,$,t),n(e,L,t),n(e,h,t),n(e,E,t),S(g,e,t),n(e,H,t),n(e,x,t),A=!0},p:I,i(e){A||(j(m.$$.fragment,e),j(p.$$.fragment,e),j(u.$$.fragment,e),j(g.$$.fragment,e),A=!0)},o(e){q(m.$$.fragment,e),q(p.$$.fragment,e),q(u.$$.fragment,e),q(g.$$.fragment,e),A=!1},d(e){e&&(a(C),a(_),a(w),a(P),a(b),a(z),a(f),a(T),a(c),a(M),a(d),a(y),a($),a(L),a(h),a(E),a(H),a(x)),a(o),R(m,e),R(p,e),R(u,e),R(g,e)}}}const le='{"title":"Modele Decoder","local":"modele-decoder","sections":[],"depth":1}';function oe(U){return J(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class fe extends K{constructor(o){super(),V(this,o,oe,re,X,{})}}export{fe as component};
