import{s as W,n as j,o as B}from"../chunks/scheduler.37c15a92.js";import{S as I,i as U,g as h,s as o,r as C,A as G,h as p,f as a,c as i,j as A,u as H,x as L,k as N,y as O,a as s,v as T,d as D,t as E,w as M}from"../chunks/index.7cb9c9b8.js";import{C as Q}from"../chunks/CourseFloatingBanner.df82c153.js";import{H as R,E as J}from"../chunks/getInferenceSnippets.48a77c36.js";function K(S){let n,$,d,b,r,_,l,w,u,q="Well, that was quite a tour through the 🤗 Datasets library — congratulations on making it this far! With the knowledge that you’ve gained from this chapter, you should be able to:",y,m,z="<li>Load datasets from anywhere, be it the Hugging Face Hub, your laptop, or a remote server at your company.</li> <li>Wrangle your data using a mix of the <code>Dataset.map()</code> and <code>Dataset.filter()</code> functions.</li> <li>Quickly switch between data formats like Pandas and NumPy using <code>Dataset.set_format()</code>.</li> <li>Create your very own dataset and push it to the Hugging Face Hub.</li> <li>Embed your documents using a Transformer model and build a semantic search engine using FAISS.</li>",v,c,F='In <a href="/course/chapter7">Chapter 7</a>, we’ll put all of this to good use as we take a deep dive into the core NLP tasks that Transformer models are great for. Before jumping ahead, though, put your knowledge of 🤗 Datasets to the test with a quick quiz!',k,f,x,g,P;return r=new R({props:{title:"🤗 Datasets, check!",local:"datasets-check",headingTag:"h1"}}),l=new Q({props:{chapter:5,classNames:"absolute z-10 right-0 top-0"}}),f=new J({props:{source:"https://github.com/huggingface/course/blob/main/chapters/en/chapter5/7.mdx"}}),{c(){n=h("meta"),$=o(),d=h("p"),b=o(),C(r.$$.fragment),_=o(),C(l.$$.fragment),w=o(),u=h("p"),u.textContent=q,y=o(),m=h("ul"),m.innerHTML=z,v=o(),c=h("p"),c.innerHTML=F,k=o(),C(f.$$.fragment),x=o(),g=h("p"),this.h()},l(t){const e=G("svelte-u9bgzb",document.head);n=p(e,"META",{name:!0,content:!0}),e.forEach(a),$=i(t),d=p(t,"P",{}),A(d).forEach(a),b=i(t),H(r.$$.fragment,t),_=i(t),H(l.$$.fragment,t),w=i(t),u=p(t,"P",{"data-svelte-h":!0}),L(u)!=="svelte-b42zfc"&&(u.textContent=q),y=i(t),m=p(t,"UL",{"data-svelte-h":!0}),L(m)!=="svelte-vwrb79"&&(m.innerHTML=z),v=i(t),c=p(t,"P",{"data-svelte-h":!0}),L(c)!=="svelte-cfae0"&&(c.innerHTML=F),k=i(t),H(f.$$.fragment,t),x=i(t),g=p(t,"P",{}),A(g).forEach(a),this.h()},h(){N(n,"name","hf:doc:metadata"),N(n,"content",V)},m(t,e){O(document.head,n),s(t,$,e),s(t,d,e),s(t,b,e),T(r,t,e),s(t,_,e),T(l,t,e),s(t,w,e),s(t,u,e),s(t,y,e),s(t,m,e),s(t,v,e),s(t,c,e),s(t,k,e),T(f,t,e),s(t,x,e),s(t,g,e),P=!0},p:j,i(t){P||(D(r.$$.fragment,t),D(l.$$.fragment,t),D(f.$$.fragment,t),P=!0)},o(t){E(r.$$.fragment,t),E(l.$$.fragment,t),E(f.$$.fragment,t),P=!1},d(t){t&&(a($),a(d),a(b),a(_),a(w),a(u),a(y),a(m),a(v),a(c),a(k),a(x),a(g)),a(n),M(r,t),M(l,t),M(f,t)}}}const V='{"title":"🤗 Datasets, check!","local":"datasets-check","sections":[],"depth":1}';function X(S){return B(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class at extends I{constructor(n){super(),U(this,n,X,K,W,{})}}export{at as component};
