course/pr_1192/ja/_app/immutable/nodes/12.2cdcc65a.js

import{s as k,n as F,o as I}from"../chunks/scheduler.ddeee2a5.js";import{S as O,i as U,e as $,s,c as y,h as X,a as c,d as n,b as i,f as D,g as M,j as S,k as N,l as J,m as a,n as w,t as B,o as A,p as H}from"../chunks/index.b5ed4bbb.js";import{C as K,H as Q,E as V}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.e12f480c.js";import{C as W}from"../chunks/CourseFloatingBanner.e70be405.js";function Y(j){let r,_,h,b,l,g,m,x,o,E,p,q="この章では、🤗 Transformersが提供する高レベルな<code>pipeline()</code> 関数を用いて、異なるNLPタスクにアプローチする方法を学びました。また、同様にHubを用いてモデルを探す方法や、推論APIを使ってブラウザ上でモデルを直接テストする方法も学びました。",L,f,z="さらに、Transformerモデルがどのように動作するかを高いレベルで議論し、さらに転移学習やファインチューニングの重要性について話しました。一つの重要な観点は、解きたいタスクに応じてアーキテクチャ全体を用いることや、エンコーダーやデコーダーの一方だけを用いることができるという点です。以下の表はそのまとめです。",C,d,G="<thead><tr><th>モデル</th> <th>例</th> <th>タスク</th></tr></thead> <tbody><tr><td>Encoder</td> <td>ALBERT, BERT, DistilBERT, ELECTRA, RoBERTa</td> <td>文章分類, 固有表現抽出, 抽出型質問応答</td></tr> <tr><td>Decoder</td> <td>CTRL, GPT, GPT-2, Transformer XL</td> <td>文章生成</td></tr> <tr><td>Encoder-decoder</td> <td>BART, T5, Marian, mBART</td> <td>文章要約, 翻訳, 生成型質問応答　</td></tr></tbody>",P,u,v,T,R;return l=new K({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),m=new Q({props:{title:"まとめ",local:"まとめ",headingTag:"h1"}}),o=new W({props:{chapter:1,classNames:"absolute z-10 right-0 top-0"}}),u=new V({props:{source:"https://github.com/huggingface/course/blob/main/chapters/ja/chapter1/9.mdx"}}),{c(){r=$("meta"),_=s(),h=$("p"),b=s(),y(l.$$.fragment),g=s(),y(m.$$.fragment),x=s(),y(o.$$.fragment),E=s(),p=$("p"),p.innerHTML=q,L=s(),f=$("p"),f.textContent=z,C=s(),d=$("table"),d.innerHTML=G,P=s(),y(u.$$.fragment),v=s(),T=$("p"),this.h()},l(t){const e=X("svelte-u9bgzb",document.head);r=c(e,"META",{name:!0,content:!0}),e.forEach(n),_=i(t),h=c(t,"P",{}),D(h).forEach(n),b=i(t),M(l.$$.fragment,t),g=i(t),M(m.$$.fragment,t),x=i(t),M(o.$$.fragment,t),E=i(t),p=c(t,"P",{"data-svelte-h":!0}),S(p)!=="svelte-mtx8ld"&&(p.innerHTML=q),L=i(t),f=c(t,"P",{"data-svelte-h":!0}),S(f)!=="svelte-1q0eqj7"&&(f.textContent=z),C=i(t),d=c(t,"TABLE",{"data-svelte-h":!0}),S(d)!=="svelte-lr3bdh"&&(d.innerHTML=G),P=i(t),M(u.$$.fragment,t),v=i(t),T=c(t,"P",{}),D(T).forEach(n),this.h()},h(){N(r,"name","hf:doc:metadata"),N(r,"content",Z)},m(t,e){J(document.head,r),a(t,_,e),a(t,h,e),a(t,b,e),w(l,t,e),a(t,g,e),w(m,t,e),a(t,x,e),w(o,t,e),a(t,E,e),a(t,p,e),a(t,L,e),a(t,f,e),a(t,C,e),a(t,d,e),a(t,P,e),w(u,t,e),a(t,v,e),a(t,T,e),R=!0},p:F,i(t){R||(B(l.$$.fragment,t),B(m.$$.fragment,t),B(o.$$.fragment,t),B(u.$$.fragment,t),R=!0)},o(t){A(l.$$.fragment,t),A(m.$$.fragment,t),A(o.$$.fragment,t),A(u.$$.fragment,t),R=!1},d(t){t&&(n(_),n(h),n(b),n(g),n(x),n(E),n(p),n(L),n(f),n(C),n(d),n(P),n(v),n(T)),n(r),H(l,t),H(m,t),H(o,t),H(u,t)}}}const Z='{"title":"まとめ","local":"まとめ","sections":[],"depth":1}';function tt(j){return I(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class st extends O{constructor(r){super(),U(this,r,tt,Y,k,{})}}export{st as component};