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<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;But what about second breakfast?&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;Don&#x27;t think he knows about second breakfast, Pip.&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;What about elevensies?&quot;</span>,
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_input = tokenizer(batch_sentences, padding=<span class="hljs-literal">True</span>, truncation=<span class="hljs-literal">True</span>, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(encoded_input)
{<span class="hljs-string">&#x27;input_ids&#x27;</span>: tensor([[<span class="hljs-number">101</span>, <span class="hljs-number">1252</span>, <span class="hljs-number">1184</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
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                      [<span class="hljs-number">101</span>, <span class="hljs-number">1327</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">5450</span>, <span class="hljs-number">23434</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]]),
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                           [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
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 <span class="hljs-string">&#x27;attention_mask&#x27;</span>: tensor([[<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
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                           [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]])}`}}),{c(){f(u.$$.fragment)},l(b){d(u.$$.fragment,b)},m(b,y){J(u,b,y),i=!0},p:Qj,i(b){i||($(u.$$.fragment,b),i=!0)},o(b){_(u.$$.fragment,b),i=!1},d(b){M(u,b)}}}function tb(U){let u,i;return u=new Dj({props:{$$slots:{default:[pb]},$$scope:{ctx:U}}}),{c(){f(u.$$.fragment)},l(b){d(u.$$.fragment,b)},m(b,y){J(u,b,y),i=!0},p(b,y){const w={};y&2&&(w.$$scope={dirty:y,ctx:b}),u.$set(w)},i(b){i||($(u.$$.fragment,b),i=!0)},o(b){_(u.$$.fragment,b),i=!1},d(b){M(u,b)}}}function rb(U){let u,i;return u=new E({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>batch_sentences = [
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;But what about second breakfast?&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;Don&#x27;t think he knows about second breakfast, Pip.&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;What about elevensies?&quot;</span>,
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_input = tokenizer(batch_sentences, padding=<span class="hljs-literal">True</span>, truncation=<span class="hljs-literal">True</span>, return_tensors=<span class="hljs-string">&quot;tf&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(encoded_input)
{<span class="hljs-string">&#x27;input_ids&#x27;</span>: &lt;tf.Tensor: shape=(<span class="hljs-number">2</span>, <span class="hljs-number">9</span>), dtype=int32, numpy=
array([[<span class="hljs-number">101</span>, <span class="hljs-number">1252</span>, <span class="hljs-number">1184</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
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       [<span class="hljs-number">101</span>, <span class="hljs-number">1327</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">5450</span>, <span class="hljs-number">23434</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]],
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       [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]], dtype=int32)&gt;,
 <span class="hljs-string">&#x27;attention_mask&#x27;</span>: &lt;tf.Tensor: shape=(<span class="hljs-number">2</span>, <span class="hljs-number">9</span>), dtype=int32, numpy=
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\uC774\uB7EC\uD55C \uBC29\uBC95\uC740 \uBAA8\uB378\uC758 \uC6D0\uC2DC \uCD9C\uB825\uC744 \uACBD\uACC4 \uC0C1\uC790\uB098 \uC138\uADF8\uBA58\uD14C\uC774\uC158 \uB9F5\uACFC \uAC19\uC740 \uC758\uBBF8 \uC788\uB294 \uC608\uCE21\uC73C\uB85C \uBCC0\uD658\uD574\uC90D\uB2C8\uB2E4.`),v.forEach(l)},m(w,v){m(w,u,v),a(u,i),a(i,b),a(u,y)},d(w){w&&l(u)}}}function jb(U){let u,i,b,y,w,v,T,I,C,V,k,A,B,Q,Y,g,G,N,F,L,x,K,D,W,Z,El,Il,Ul,ss,as,is,kl,fr,dr,la,Jr,Cl,$r,_r,He,ks,Oe,Zl,Mr,Le,na,Ke,fs,Cs,Mn,ea,yr,yn,wr,sp,pa,ap,ls,vr,Gl,gr,Tr,wn,Er,Ir,lp,Zs,np,ns,Ur,vn,kr,Cr,gn,Zr,Gr,ep,ta,pp,Vl,Vr,tp,ra,rp,Bl,Br,cp,es,Wl,Al,Wr,Ar,Nr,Nl,xl,xr,Rr,Xr,Rl,Xl,Yr,Fr,mp,ca,Tn,zr,qr,op,ma,hp,ps,Qr,En,Dr,Pr,In,Sr,Hr,up,Yl,Or,jp,oa,bp,ds,Gs,Un,ha,Lr,kn,Kr,ip,Vs,sc,Cn,ac,lc,fp,Js,Zn,nc,ec,Gn,pc,tc,dp,ua,Jp,Bs,rc,Vn,cc,mc,$p,$s,Ws,Bn,ja,oc,Wn,hc,_p,Fl,uc,Mp,ts,jc,An,bc,ic,Nn,fc,dc,yp,ba,wp,As,vp,_s,Ns,xn,ia,Jc,Rn,$c,gp,zl,_c,Tp,P,Xn,Mc,yc,Yn,wc,vc,Fn,gc,Tc,Ep,xs,Ip,Ms,Rs,zn,fa,Ec,qn,Ic,Up,Xs,Uc,ql,kc,Cc,kp,rs,Zc,da,Gc,Vc,Ja,Bc,Wc,Cp,$a,Zp,ys,Qn,Ac,Nc,Dn,xc,Rc,Gp,_a,Vp,Ql,Xc,Bp,cs,Dl,Pn,Yc,Fc,zc,Pl,Sn,qc,Qc,Dc,Sl,Hn,Pc,Sc,Wp,Ys,Hc,Ma,Oc,Lc,Ap,Hl,ya,Kc,On,sm,am,Np,wa,xp,va,ga,lm,Ln,nm,em,Rp,Ta,Xp,ms,pm,Kn,tm,rm,se,cm,mm,Yp,Ea,ae,om,hm,Fp,Ia,zp,os,um,le,jm,bm,ne,im,fm,qp,Ua,Qp,Ol,dm,Dp,ka,Pp,Ll,Jm,Sp,Ca,Hp,Za,ee,$m,_m,Op,Ga,Lp,Kl,Mm,Kp,Va,st,ws,Fs,pe,Ba,ym,te,wm,at,zs,vm,sn,gm,Tm,lt,qs,nt,vs,Wa,Em,Im,Aa,Um,km,et,Qs,pt,Na,tt,Ds,Cm,xa,re,Zm,Gm,rt,Ra,ct,Xa,ce,yh,mt,Ya,me,Vm,Bm,ot,Fa,ht,z,Wm,za,oe,Am,Nm,qa,xm,Rm,Qa,Xm,Ym,ut,an,R,Da,he,Fm,zm,Pa,ue,qm,Qm,Sa,je,Dm,Pm,be,Sm,Hm,ie,Om,Lm,jt,Ha,bt,Oa,S,Km,ln,fe,so,ao,de,lo,no,Je,eo,po,it,La,ft,Ps,dt,Ka,sl,to,al,$e,ro,co,Jt,ll,$t,nl,el,mo,_e,oo,ho,_t,pl,Mt,nn,uo,yt,tl,wt,rl,Me,wh,vt,Ss,gt,gs,Hs,ye,cl,jo,we,bo,Tt,X,io,en,fo,Jo,ve,$o,_o,ge,Mo,yo,Te,wo,vo,Et,ml,It,Ts,Os,Ee,ol,go,Ie,To,Ut,Ls,Eo,pn,Io,Uo,kt,Es,hl,ko,Co,ul,Zo,Go,Ct,jl,Zt,hs,Vo,Ue,Bo,Wo,ke,Ao,No,Gt,bl,Vt,us,xo,Ce,Ro,Xo,Ze,Yo,Fo,Bt,il,Wt,Ks,zo,tn,qo,Qo,At,fl,Nt,dl,Ge,Do,Po,xt,Jl,Rt,rn,q,Ve,So,Ho,Be,Oo,Lo,We,Ko,sh,Ae,ah,lh,Xt,$l,Yt,_l,Ml,nh,Ne,eh,ph,Ft,yl,zt,js,th,xe,rh,ch,Re,mh,oh,qt;return v=new Us({}),k=new sb({props:{classNames:"absolute z-10 right-0 top-0",options:[{label:"Mixed",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/ko/preprocessing.ipynb"},{label:"PyTorch",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/ko/pytorch/preprocessing.ipynb"},{label:"TensorFlow",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/ko/tensorflow/preprocessing.ipynb"},{label:"Mixed",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/ko/preprocessing.ipynb"},{label:"PyTorch",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/ko/pytorch/preprocessing.ipynb"},{label:"TensorFlow",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/ko/tensorflow/preprocessing.ipynb"}]}}),ks=new Tl({props:{$$slots:{default:[lb]},$$scope:{ctx:U}}}),na=new E({props:{code:"cGlwJTIwaW5zdGFsbCUyMGRhdGFzZXRz",highlighted:"pip install datasets"}}),ea=new Us({}),pa=new Kj({props:{id:"Yffk5aydLzg"}}),Zs=new Tl({props:{$$slots:{default:[nb]},$$scope:{ctx:U}}}),ta=new E({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9Ub2tlbml6ZXIlMEElMEF0b2tlbml6ZXIlMjAlM0QlMjBBdXRvVG9rZW5pemVyLmZyb21fcHJldHJhaW5lZCglMjJiZXJ0LWJhc2UtY2FzZWQlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;bert-base-cased&quot;</span>)`}}),ra=new E({props:{code:"ZW5jb2RlZF9pbnB1dCUyMCUzRCUyMHRva2VuaXplciglMjJEbyUyMG5vdCUyMG1lZGRsZSUyMGluJTIwdGhlJTIwYWZmYWlycyUyMG9mJTIwd2l6YXJkcyUyQyUyMGZvciUyMHRoZXklMjBhcmUlMjBzdWJ0bGUlMjBhbmQlMjBxdWljayUyMHRvJTIwYW5nZXIuJTIyKSUwQXByaW50KGVuY29kZWRfaW5wdXQp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_input = tokenizer(<span class="hljs-string">&quot;Do not meddle in the affairs of wizards, for they are subtle and quick to anger.&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(encoded_input)
{<span class="hljs-string">&#x27;input_ids&#x27;</span>: [<span class="hljs-number">101</span>, <span class="hljs-number">2079</span>, <span class="hljs-number">2025</span>, <span class="hljs-number">19960</span>, <span class="hljs-number">10362</span>, <span class="hljs-number">1999</span>, <span class="hljs-number">1996</span>, <span class="hljs-number">3821</span>, <span class="hljs-number">1997</span>, <span class="hljs-number">16657</span>, <span class="hljs-number">1010</span>, <span class="hljs-number">2005</span>, <span class="hljs-number">2027</span>, <span class="hljs-number">2024</span>, <span class="hljs-number">11259</span>, <span class="hljs-number">1998</span>, <span class="hljs-number">4248</span>, <span class="hljs-number">2000</span>, <span class="hljs-number">4963</span>, <span class="hljs-number">1012</span>, <span class="hljs-number">102</span>],
 <span class="hljs-string">&#x27;token_type_ids&#x27;</span>: [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
 <span class="hljs-string">&#x27;attention_mask&#x27;</span>: [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>]}`}}),ma=new E({props:{code:"dG9rZW5pemVyLmRlY29kZShlbmNvZGVkX2lucHV0JTVCJTIyaW5wdXRfaWRzJTIyJTVEKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer.decode(encoded_input[<span class="hljs-string">&quot;input_ids&quot;</span>])
<span class="hljs-string">&#x27;[CLS] Do not meddle in the affairs of wizards, for they are subtle and quick to anger. [SEP]&#x27;</span>`}}),oa=new E({props:{code:"YmF0Y2hfc2VudGVuY2VzJTIwJTNEJTIwJTVCJTBBJTIwJTIwJTIwJTIwJTIyQnV0JTIwd2hhdCUyMGFib3V0JTIwc2Vjb25kJTIwYnJlYWtmYXN0JTNGJTIyJTJDJTBBJTIwJTIwJTIwJTIwJTIyRG9uJ3QlMjB0aGluayUyMGhlJTIwa25vd3MlMjBhYm91dCUyMHNlY29uZCUyMGJyZWFrZmFzdCUyQyUyMFBpcC4lMjIlMkMlMEElMjAlMjAlMjAlMjAlMjJXaGF0JTIwYWJvdXQlMjBlbGV2ZW5zaWVzJTNGJTIyJTJDJTBBJTVEJTBBZW5jb2RlZF9pbnB1dHMlMjAlM0QlMjB0b2tlbml6ZXIoYmF0Y2hfc2VudGVuY2VzKSUwQXByaW50KGVuY29kZWRfaW5wdXRzKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>batch_sentences = [
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;But what about second breakfast?&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;Don&#x27;t think he knows about second breakfast, Pip.&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;What about elevensies?&quot;</span>,
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_inputs = tokenizer(batch_sentences)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(encoded_inputs)
{<span class="hljs-string">&#x27;input_ids&#x27;</span>: [[<span class="hljs-number">101</span>, <span class="hljs-number">1252</span>, <span class="hljs-number">1184</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>],
               [<span class="hljs-number">101</span>, <span class="hljs-number">1790</span>, <span class="hljs-number">112</span>, <span class="hljs-number">189</span>, <span class="hljs-number">1341</span>, <span class="hljs-number">1119</span>, <span class="hljs-number">3520</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">117</span>, <span class="hljs-number">21902</span>, <span class="hljs-number">1643</span>, <span class="hljs-number">119</span>, <span class="hljs-number">102</span>],
               [<span class="hljs-number">101</span>, <span class="hljs-number">1327</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">5450</span>, <span class="hljs-number">23434</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>]],
 <span class="hljs-string">&#x27;token_type_ids&#x27;</span>: [[<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]],
 <span class="hljs-string">&#x27;attention_mask&#x27;</span>: [[<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>],
                    [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>],
                    [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>]]}`}}),ha=new Us({}),ua=new E({props:{code:"YmF0Y2hfc2VudGVuY2VzJTIwJTNEJTIwJTVCJTBBJTIwJTIwJTIwJTIwJTIyQnV0JTIwd2hhdCUyMGFib3V0JTIwc2Vjb25kJTIwYnJlYWtmYXN0JTNGJTIyJTJDJTBBJTIwJTIwJTIwJTIwJTIyRG9uJ3QlMjB0aGluayUyMGhlJTIwa25vd3MlMjBhYm91dCUyMHNlY29uZCUyMGJyZWFrZmFzdCUyQyUyMFBpcC4lMjIlMkMlMEElMjAlMjAlMjAlMjAlMjJXaGF0JTIwYWJvdXQlMjBlbGV2ZW5zaWVzJTNGJTIyJTJDJTBBJTVEJTBBZW5jb2RlZF9pbnB1dCUyMCUzRCUyMHRva2VuaXplcihiYXRjaF9zZW50ZW5jZXMlMkMlMjBwYWRkaW5nJTNEVHJ1ZSklMEFwcmludChlbmNvZGVkX2lucHV0KQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>batch_sentences = [
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;But what about second breakfast?&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;Don&#x27;t think he knows about second breakfast, Pip.&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;What about elevensies?&quot;</span>,
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_input = tokenizer(batch_sentences, padding=<span class="hljs-literal">True</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(encoded_input)
{<span class="hljs-string">&#x27;input_ids&#x27;</span>: [[<span class="hljs-number">101</span>, <span class="hljs-number">1252</span>, <span class="hljs-number">1184</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
               [<span class="hljs-number">101</span>, <span class="hljs-number">1790</span>, <span class="hljs-number">112</span>, <span class="hljs-number">189</span>, <span class="hljs-number">1341</span>, <span class="hljs-number">1119</span>, <span class="hljs-number">3520</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">117</span>, <span class="hljs-number">21902</span>, <span class="hljs-number">1643</span>, <span class="hljs-number">119</span>, <span class="hljs-number">102</span>],
               [<span class="hljs-number">101</span>, <span class="hljs-number">1327</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">5450</span>, <span class="hljs-number">23434</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]],
 <span class="hljs-string">&#x27;token_type_ids&#x27;</span>: [[<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]],
 <span class="hljs-string">&#x27;attention_mask&#x27;</span>: [[<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>],
                    [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]]}`}}),ja=new Us({}),ba=new E({props:{code:"YmF0Y2hfc2VudGVuY2VzJTIwJTNEJTIwJTVCJTBBJTIwJTIwJTIwJTIwJTIyQnV0JTIwd2hhdCUyMGFib3V0JTIwc2Vjb25kJTIwYnJlYWtmYXN0JTNGJTIyJTJDJTBBJTIwJTIwJTIwJTIwJTIyRG9uJ3QlMjB0aGluayUyMGhlJTIwa25vd3MlMjBhYm91dCUyMHNlY29uZCUyMGJyZWFrZmFzdCUyQyUyMFBpcC4lMjIlMkMlMEElMjAlMjAlMjAlMjAlMjJXaGF0JTIwYWJvdXQlMjBlbGV2ZW5zaWVzJTNGJTIyJTJDJTBBJTVEJTBBZW5jb2RlZF9pbnB1dCUyMCUzRCUyMHRva2VuaXplcihiYXRjaF9zZW50ZW5jZXMlMkMlMjBwYWRkaW5nJTNEVHJ1ZSUyQyUyMHRydW5jYXRpb24lM0RUcnVlKSUwQXByaW50KGVuY29kZWRfaW5wdXQp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>batch_sentences = [
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;But what about second breakfast?&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;Don&#x27;t think he knows about second breakfast, Pip.&quot;</span>,
<span class="hljs-meta">... </span>    <span class="hljs-string">&quot;What about elevensies?&quot;</span>,
<span class="hljs-meta">... </span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_input = tokenizer(batch_sentences, padding=<span class="hljs-literal">True</span>, truncation=<span class="hljs-literal">True</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(encoded_input)
{<span class="hljs-string">&#x27;input_ids&#x27;</span>: [[<span class="hljs-number">101</span>, <span class="hljs-number">1252</span>, <span class="hljs-number">1184</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
               [<span class="hljs-number">101</span>, <span class="hljs-number">1790</span>, <span class="hljs-number">112</span>, <span class="hljs-number">189</span>, <span class="hljs-number">1341</span>, <span class="hljs-number">1119</span>, <span class="hljs-number">3520</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">1248</span>, <span class="hljs-number">6462</span>, <span class="hljs-number">117</span>, <span class="hljs-number">21902</span>, <span class="hljs-number">1643</span>, <span class="hljs-number">119</span>, <span class="hljs-number">102</span>],
               [<span class="hljs-number">101</span>, <span class="hljs-number">1327</span>, <span class="hljs-number">1164</span>, <span class="hljs-number">5450</span>, <span class="hljs-number">23434</span>, <span class="hljs-number">136</span>, <span class="hljs-number">102</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]],
 <span class="hljs-string">&#x27;token_type_ids&#x27;</span>: [[<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]],
 <span class="hljs-string">&#x27;attention_mask&#x27;</span>: [[<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
                    [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>],
                    [<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>]]}`}}),As=new Tl({props:{$$slots:{default:[eb]},$$scope:{ctx:U}}}),ia=new Us({}),xs=new ab({props:{pytorch:!0,tensorflow:!0,jax:!1,$$slots:{tensorflow:[cb],pytorch:[tb]},$$scope:{ctx:U}}}),fa=new Us({}),$a=new E({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTJDJTIwQXVkaW8lMEElMEFkYXRhc2V0JTIwJTNEJTIwbG9hZF9kYXRhc2V0KCUyMlBvbHlBSSUyRm1pbmRzMTQlMjIlMkMlMjBuYW1lJTNEJTIyZW4tVVMlMjIlMkMlMjBzcGxpdCUzRCUyMnRyYWluJTIyKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset, Audio

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;PolyAI/minds14&quot;</span>, name=<span class="hljs-string">&quot;en-US&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)`}}),_a=new E({props:{code:"ZGF0YXNldCU1QjAlNUQlNUIlMjJhdWRpbyUyMiU1RA==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;audio&quot;</span>]
{<span class="hljs-string">&#x27;array&#x27;</span>: array([ <span class="hljs-number">0.</span>        ,  <span class="hljs-number">0.00024414</span>, -<span class="hljs-number">0.00024414</span>, ..., -<span class="hljs-number">0.00024414</span>,
         <span class="hljs-number">0.</span>        ,  <span class="hljs-number">0.</span>        ], dtype=float32),
 <span class="hljs-string">&#x27;path&#x27;</span>: <span class="hljs-string">&#x27;/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav&#x27;</span>,
 <span class="hljs-string">&#x27;sampling_rate&#x27;</span>: <span class="hljs-number">8000</span>}`}}),wa=new E({props:{code:"ZGF0YXNldCUyMCUzRCUyMGRhdGFzZXQuY2FzdF9jb2x1bW4oJTIyYXVkaW8lMjIlMkMlMjBBdWRpbyhzYW1wbGluZ19yYXRlJTNEMTZfMDAwKSk=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = dataset.cast_column(<span class="hljs-string">&quot;audio&quot;</span>, Audio(sampling_rate=<span class="hljs-number">16_000</span>))'}}),Ta=new E({props:{code:"ZGF0YXNldCU1QjAlNUQlNUIlMjJhdWRpbyUyMiU1RA==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;audio&quot;</span>]
{<span class="hljs-string">&#x27;array&#x27;</span>: array([ <span class="hljs-number">2.3443763e-05</span>,  <span class="hljs-number">2.1729663e-04</span>,  <span class="hljs-number">2.2145823e-04</span>, ...,
         <span class="hljs-number">3.8356509e-05</span>, -<span class="hljs-number">7.3497440e-06</span>, -<span class="hljs-number">2.1754686e-05</span>], dtype=float32),
 <span class="hljs-string">&#x27;path&#x27;</span>: <span class="hljs-string">&#x27;/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav&#x27;</span>,
 <span class="hljs-string">&#x27;sampling_rate&#x27;</span>: <span class="hljs-number">16000</span>}`}}),Ia=new E({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9GZWF0dXJlRXh0cmFjdG9yJTBBJTBBZmVhdHVyZV9leHRyYWN0b3IlMjAlM0QlMjBBdXRvRmVhdHVyZUV4dHJhY3Rvci5mcm9tX3ByZXRyYWluZWQoJTIyZmFjZWJvb2slMkZ3YXYydmVjMi1iYXNlJTIyKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoFeatureExtractor

<span class="hljs-meta">&gt;&gt;&gt; </span>feature_extractor = AutoFeatureExtractor.from_pretrained(<span class="hljs-string">&quot;facebook/wav2vec2-base&quot;</span>)`}}),Ua=new E({props:{code:"YXVkaW9faW5wdXQlMjAlM0QlMjAlNUJkYXRhc2V0JTVCMCU1RCU1QiUyMmF1ZGlvJTIyJTVEJTVCJTIyYXJyYXklMjIlNUQlNUQlMEFmZWF0dXJlX2V4dHJhY3RvcihhdWRpb19pbnB1dCUyQyUyMHNhbXBsaW5nX3JhdGUlM0QxNjAwMCk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>audio_input = [dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;audio&quot;</span>][<span class="hljs-string">&quot;array&quot;</span>]]
<span class="hljs-meta">&gt;&gt;&gt; </span>feature_extractor(audio_input, sampling_rate=<span class="hljs-number">16000</span>)
{<span class="hljs-string">&#x27;input_values&#x27;</span>: [array([ <span class="hljs-number">3.8106556e-04</span>,  <span class="hljs-number">2.7506407e-03</span>,  <span class="hljs-number">2.8015103e-03</span>, ...,
        <span class="hljs-number">5.6335266e-04</span>,  <span class="hljs-number">4.6588284e-06</span>, -<span class="hljs-number">1.7142107e-04</span>], dtype=float32)]}`}}),ka=new E({props:{code:"ZGF0YXNldCU1QjAlNUQlNUIlMjJhdWRpbyUyMiU1RCU1QiUyMmFycmF5JTIyJTVELnNoYXBlJTBBJTBBZGF0YXNldCU1QjElNUQlNUIlMjJhdWRpbyUyMiU1RCU1QiUyMmFycmF5JTIyJTVELnNoYXBl",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;audio&quot;</span>][<span class="hljs-string">&quot;array&quot;</span>].shape
(<span class="hljs-number">173398</span>,)

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">1</span>][<span class="hljs-string">&quot;audio&quot;</span>][<span class="hljs-string">&quot;array&quot;</span>].shape
(<span class="hljs-number">106496</span>,)`}}),Ca=new E({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">def</span> <span class="hljs-title function_">preprocess_function</span>(<span class="hljs-params">examples</span>):
<span class="hljs-meta">... </span>    audio_arrays = [x[<span class="hljs-string">&quot;array&quot;</span>] <span class="hljs-keyword">for</span> x <span class="hljs-keyword">in</span> examples[<span class="hljs-string">&quot;audio&quot;</span>]]
<span class="hljs-meta">... </span>    inputs = feature_extractor(
<span class="hljs-meta">... </span>        audio_arrays,
<span class="hljs-meta">... </span>        sampling_rate=<span class="hljs-number">16000</span>,
<span class="hljs-meta">... </span>        padding=<span class="hljs-literal">True</span>,
<span class="hljs-meta">... </span>        max_length=<span class="hljs-number">100000</span>,
<span class="hljs-meta">... </span>        truncation=<span class="hljs-literal">True</span>,
<span class="hljs-meta">... </span>    )
<span class="hljs-meta">... </span>    <span class="hljs-keyword">return</span> inputs`}}),Ga=new E({props:{code:"cHJvY2Vzc2VkX2RhdGFzZXQlMjAlM0QlMjBwcmVwcm9jZXNzX2Z1bmN0aW9uKGRhdGFzZXQlNUIlM0E1JTVEKQ==",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>processed_dataset = preprocess_function(dataset[:<span class="hljs-number">5</span>])'}}),Va=new E({props:{code:"cHJvY2Vzc2VkX2RhdGFzZXQlNUIlMjJpbnB1dF92YWx1ZXMlMjIlNUQlNUIwJTVELnNoYXBlJTBBJTBBcHJvY2Vzc2VkX2RhdGFzZXQlNUIlMjJpbnB1dF92YWx1ZXMlMjIlNUQlNUIxJTVELnNoYXBl",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>processed_dataset[<span class="hljs-string">&quot;input_values&quot;</span>][<span class="hljs-number">0</span>].shape
(<span class="hljs-number">100000</span>,)

<span class="hljs-meta">&gt;&gt;&gt; </span>processed_dataset[<span class="hljs-string">&quot;input_values&quot;</span>][<span class="hljs-number">1</span>].shape
(<span class="hljs-number">100000</span>,)`}}),Ba=new Us({}),qs=new Tl({props:{$$slots:{default:[mb]},$$scope:{ctx:U}}}),Qs=new Tl({props:{$$slots:{default:[ob]},$$scope:{ctx:U}}}),Na=new E({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBJTBBZGF0YXNldCUyMCUzRCUyMGxvYWRfZGF0YXNldCglMjJmb29kMTAxJTIyJTJDJTIwc3BsaXQlM0QlMjJ0cmFpbiU1QiUzQTEwMCU1RCUyMik=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;food101&quot;</span>, split=<span class="hljs-string">&quot;train[:100]&quot;</span>)`}}),Ra=new E({props:{code:"ZGF0YXNldCU1QjAlNUQlNUIlMjJpbWFnZSUyMiU1RA==",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;image&quot;</span>]'}}),Fa=new E({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9JbWFnZVByb2Nlc3NvciUwQSUwQWltYWdlX3Byb2Nlc3NvciUyMCUzRCUyMEF1dG9JbWFnZVByb2Nlc3Nvci5mcm9tX3ByZXRyYWluZWQoJTIyZ29vZ2xlJTJGdml0LWJhc2UtcGF0Y2gxNi0yMjQlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoImageProcessor

<span class="hljs-meta">&gt;&gt;&gt; </span>image_processor = AutoImageProcessor.from_pretrained(<span class="hljs-string">&quot;google/vit-base-patch16-224&quot;</span>)`}}),Ha=new E({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> torchvision.transforms <span class="hljs-keyword">import</span> RandomResizedCrop, ColorJitter, Compose

<span class="hljs-meta">&gt;&gt;&gt; </span>size = (
<span class="hljs-meta">... </span>    image_processor.size[<span class="hljs-string">&quot;shortest_edge&quot;</span>]
<span class="hljs-meta">... </span>    <span class="hljs-keyword">if</span> <span class="hljs-string">&quot;shortest_edge&quot;</span> <span class="hljs-keyword">in</span> image_processor.size
<span class="hljs-meta">... </span>    <span class="hljs-keyword">else</span> (image_processor.size[<span class="hljs-string">&quot;height&quot;</span>], image_processor.size[<span class="hljs-string">&quot;width&quot;</span>])
<span class="hljs-meta">... </span>)

<span class="hljs-meta">&gt;&gt;&gt; </span>_transforms = Compose([RandomResizedCrop(size), ColorJitter(brightness=<span class="hljs-number">0.5</span>, hue=<span class="hljs-number">0.5</span>)])`}}),La=new E({props:{code:"ZGVmJTIwdHJhbnNmb3JtcyhleGFtcGxlcyklM0ElMEElMjAlMjAlMjAlMjBpbWFnZXMlMjAlM0QlMjAlNUJfdHJhbnNmb3JtcyhpbWcuY29udmVydCglMjJSR0IlMjIpKSUyMGZvciUyMGltZyUyMGluJTIwZXhhbXBsZXMlNUIlMjJpbWFnZSUyMiU1RCU1RCUwQSUyMCUyMCUyMCUyMGV4YW1wbGVzJTVCJTIycGl4ZWxfdmFsdWVzJTIyJTVEJTIwJTNEJTIwaW1hZ2VfcHJvY2Vzc29yKGltYWdlcyUyQyUyMGRvX3Jlc2l6ZSUzREZhbHNlJTJDJTIwcmV0dXJuX3RlbnNvcnMlM0QlMjJwdCUyMiklNUIlMjJwaXhlbF92YWx1ZXMlMjIlNUQlMEElMjAlMjAlMjAlMjByZXR1cm4lMjBleGFtcGxlcw==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">def</span> <span class="hljs-title function_">transforms</span>(<span class="hljs-params">examples</span>):
<span class="hljs-meta">... </span>    images = [_transforms(img.convert(<span class="hljs-string">&quot;RGB&quot;</span>)) <span class="hljs-keyword">for</span> img <span class="hljs-keyword">in</span> examples[<span class="hljs-string">&quot;image&quot;</span>]]
<span class="hljs-meta">... </span>    examples[<span class="hljs-string">&quot;pixel_values&quot;</span>] = image_processor(images, do_resize=<span class="hljs-literal">False</span>, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)[<span class="hljs-string">&quot;pixel_values&quot;</span>]
<span class="hljs-meta">... </span>    <span class="hljs-keyword">return</span> examples`}}),Ps=new Tl({props:{$$slots:{default:[hb]},$$scope:{ctx:U}}}),ll=new E({props:{code:"ZGF0YXNldC5zZXRfdHJhbnNmb3JtKHRyYW5zZm9ybXMp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>dataset.set_transform(transforms)'}}),pl=new E({props:{code:"ZGF0YXNldCU1QjAlNUQua2V5cygp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>].keys()'}}),tl=new E({props:{code:"aW1wb3J0JTIwbnVtcHklMjBhcyUyMG5wJTBBaW1wb3J0JTIwbWF0cGxvdGxpYi5weXBsb3QlMjBhcyUyMHBsdCUwQSUwQWltZyUyMCUzRCUyMGRhdGFzZXQlNUIwJTVEJTVCJTIycGl4ZWxfdmFsdWVzJTIyJTVEJTBBcGx0Lmltc2hvdyhpbWcucGVybXV0ZSgxJTJDJTIwMiUyQyUyMDApKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt

<span class="hljs-meta">&gt;&gt;&gt; </span>img = dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;pixel_values&quot;</span>]
<span class="hljs-meta">&gt;&gt;&gt; </span>plt.imshow(img.permute(<span class="hljs-number">1</span>, <span class="hljs-number">2</span>, <span class="hljs-number">0</span>))`}}),Ss=new Tl({props:{$$slots:{default:[ub]},$$scope:{ctx:U}}}),cl=new Us({}),ml=new E({props:{code:"ZGVmJTIwY29sbGF0ZV9mbihiYXRjaCklM0ElMEElMjAlMjAlMjAlMjBwaXhlbF92YWx1ZXMlMjAlM0QlMjAlNUJpdGVtJTVCJTIycGl4ZWxfdmFsdWVzJTIyJTVEJTIwZm9yJTIwaXRlbSUyMGluJTIwYmF0Y2glNUQlMEElMjAlMjAlMjAlMjBlbmNvZGluZyUyMCUzRCUyMGltYWdlX3Byb2Nlc3Nvci5wYWQocGl4ZWxfdmFsdWVzJTJDJTIwcmV0dXJuX3RlbnNvcnMlM0QlMjJwdCUyMiklMEElMjAlMjAlMjAlMjBsYWJlbHMlMjAlM0QlMjAlNUJpdGVtJTVCJTIybGFiZWxzJTIyJTVEJTIwZm9yJTIwaXRlbSUyMGluJTIwYmF0Y2glNUQlMEElMjAlMjAlMjAlMjBiYXRjaCUyMCUzRCUyMCU3QiU3RCUwQSUyMCUyMCUyMCUyMGJhdGNoJTVCJTIycGl4ZWxfdmFsdWVzJTIyJTVEJTIwJTNEJTIwZW5jb2RpbmclNUIlMjJwaXhlbF92YWx1ZXMlMjIlNUQlMEElMjAlMjAlMjAlMjBiYXRjaCU1QiUyMnBpeGVsX21hc2slMjIlNUQlMjAlM0QlMjBlbmNvZGluZyU1QiUyMnBpeGVsX21hc2slMjIlNUQlMEElMjAlMjAlMjAlMjBiYXRjaCU1QiUyMmxhYmVscyUyMiU1RCUyMCUzRCUyMGxhYmVscyUwQSUyMCUyMCUyMCUyMHJldHVybiUyMGJhdGNo",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">def</span> <span class="hljs-title function_">collate_fn</span>(<span class="hljs-params">batch</span>):
<span class="hljs-meta">... </span>    pixel_values = [item[<span class="hljs-string">&quot;pixel_values&quot;</span>] <span class="hljs-keyword">for</span> item <span class="hljs-keyword">in</span> batch]
<span class="hljs-meta">... </span>    encoding = image_processor.pad(pixel_values, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)
<span class="hljs-meta">... </span>    labels = [item[<span class="hljs-string">&quot;labels&quot;</span>] <span class="hljs-keyword">for</span> item <span class="hljs-keyword">in</span> batch]
<span class="hljs-meta">... </span>    batch = {}
<span class="hljs-meta">... </span>    batch[<span class="hljs-string">&quot;pixel_values&quot;</span>] = encoding[<span class="hljs-string">&quot;pixel_values&quot;</span>]
<span class="hljs-meta">... </span>    batch[<span class="hljs-string">&quot;pixel_mask&quot;</span>] = encoding[<span class="hljs-string">&quot;pixel_mask&quot;</span>]
<span class="hljs-meta">... </span>    batch[<span class="hljs-string">&quot;labels&quot;</span>] = labels
<span class="hljs-meta">... </span>    <span class="hljs-keyword">return</span> batch`}}),ol=new Us({}),jl=new E({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBJTBBbGpfc3BlZWNoJTIwJTNEJTIwbG9hZF9kYXRhc2V0KCUyMmxqX3NwZWVjaCUyMiUyQyUyMHNwbGl0JTNEJTIydHJhaW4lMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

<span class="hljs-meta">&gt;&gt;&gt; </span>lj_speech = load_dataset(<span class="hljs-string">&quot;lj_speech&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)`}}),bl=new E({props:{code:"bGpfc3BlZWNoJTIwJTNEJTIwbGpfc3BlZWNoLm1hcChyZW1vdmVfY29sdW1ucyUzRCU1QiUyMmZpbGUlMjIlMkMlMjAlMjJpZCUyMiUyQyUyMCUyMm5vcm1hbGl6ZWRfdGV4dCUyMiU1RCk=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>lj_speech = lj_speech.<span class="hljs-built_in">map</span>(remove_columns=[<span class="hljs-string">&quot;file&quot;</span>, <span class="hljs-string">&quot;id&quot;</span>, <span class="hljs-string">&quot;normalized_text&quot;</span>])'}}),il=new E({props:{code:"bGpfc3BlZWNoJTVCMCU1RCU1QiUyMmF1ZGlvJTIyJTVEJTBBJTBBbGpfc3BlZWNoJTVCMCU1RCU1QiUyMnRleHQlMjIlNUQ=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>lj_speech[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;audio&quot;</span>]
{<span class="hljs-string">&#x27;array&#x27;</span>: array([-<span class="hljs-number">7.3242188e-04</span>, -<span class="hljs-number">7.6293945e-04</span>, -<span class="hljs-number">6.4086914e-04</span>, ...,
         <span class="hljs-number">7.3242188e-04</span>,  <span class="hljs-number">2.1362305e-04</span>,  <span class="hljs-number">6.1035156e-05</span>], dtype=float32),
 <span class="hljs-string">&#x27;path&#x27;</span>: <span class="hljs-string">&#x27;/root/.cache/huggingface/datasets/downloads/extracted/917ece08c95cf0c4115e45294e3cd0dee724a1165b7fc11798369308a465bd26/LJSpeech-1.1/wavs/LJ001-0001.wav&#x27;</span>,
 <span class="hljs-string">&#x27;sampling_rate&#x27;</span>: <span class="hljs-number">22050</span>}

<span class="hljs-meta">&gt;&gt;&gt; </span>lj_speech[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;text&quot;</span>]
<span class="hljs-string">&#x27;Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition&#x27;</span>`}}),fl=new E({props:{code:"bGpfc3BlZWNoJTIwJTNEJTIwbGpfc3BlZWNoLmNhc3RfY29sdW1uKCUyMmF1ZGlvJTIyJTJDJTIwQXVkaW8oc2FtcGxpbmdfcmF0ZSUzRDE2XzAwMCkp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>lj_speech = lj_speech.cast_column(<span class="hljs-string">&quot;audio&quot;</span>, Audio(sampling_rate=<span class="hljs-number">16_000</span>))'}}),Jl=new E({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9Qcm9jZXNzb3IlMEElMEFwcm9jZXNzb3IlMjAlM0QlMjBBdXRvUHJvY2Vzc29yLmZyb21fcHJldHJhaW5lZCglMjJmYWNlYm9vayUyRndhdjJ2ZWMyLWJhc2UtOTYwaCUyMik=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoProcessor

<span class="hljs-meta">&gt;&gt;&gt; </span>processor = AutoProcessor.from_pretrained(<span class="hljs-string">&quot;facebook/wav2vec2-base-960h&quot;</span>)`}}),$l=new E({props:{code:"ZGVmJTIwcHJlcGFyZV9kYXRhc2V0KGV4YW1wbGUpJTNBJTBBJTIwJTIwJTIwJTIwYXVkaW8lMjAlM0QlMjBleGFtcGxlJTVCJTIyYXVkaW8lMjIlNUQlMEElMEElMjAlMjAlMjAlMjBleGFtcGxlLnVwZGF0ZShwcm9jZXNzb3IoYXVkaW8lM0RhdWRpbyU1QiUyMmFycmF5JTIyJTVEJTJDJTIwdGV4dCUzRGV4YW1wbGUlNUIlMjJ0ZXh0JTIyJTVEJTJDJTIwc2FtcGxpbmdfcmF0ZSUzRDE2MDAwKSklMEElMEElMjAlMjAlMjAlMjByZXR1cm4lMjBleGFtcGxl",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">def</span> <span class="hljs-title function_">prepare_dataset</span>(<span class="hljs-params">example</span>):
<span class="hljs-meta">... </span>    audio = example[<span class="hljs-string">&quot;audio&quot;</span>]

<span class="hljs-meta">... </span>    example.update(processor(audio=audio[<span class="hljs-string">&quot;array&quot;</span>], text=example[<span class="hljs-string">&quot;text&quot;</span>], sampling_rate=<span class="hljs-number">16000</span>))

<span class="hljs-meta">... </span>    <span class="hljs-keyword">return</span> example`}}),yl=new E({props:{code:"cHJlcGFyZV9kYXRhc2V0KGxqX3NwZWVjaCU1QjAlNUQp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>prepare_dataset(lj_speech[<span class="hljs-number">0</span>])'}}),{c(){u=t("meta"),i=o(),b=t("h1"),y=t("a"),w=t("span"),f(v.$$.fragment),T=o(),I=t("span"),C=n("\uC804\uCC98\uB9AC"),V=o(),f(k.$$.fragment),A=o(),B=t("p"),Q=n("\uBAA8\uB378\uC744 \uD6C8\uB828\uD558\uB824\uBA74 \uB370\uC774\uD130 \uC138\uD2B8\uB97C \uBAA8\uB378\uC5D0 \uB9DE\uB294 \uC785\uB825 \uD615\uC2DD\uC73C\uB85C \uC804\uCC98\uB9AC\uD574\uC57C \uD569\uB2C8\uB2E4. \uD14D\uC2A4\uD2B8, \uC774\uBBF8\uC9C0 \uB610\uB294 \uC624\uB514\uC624\uC778\uC9C0 \uAD00\uACC4\uC5C6\uC774 \uB370\uC774\uD130\uB97C \uD150\uC11C \uBC30\uCE58\uB85C \uBCC0\uD658\uD558\uACE0 \uC870\uB9BD\uD560 \uD544\uC694\uAC00 \uC788\uC2B5\uB2C8\uB2E4. \u{1F917} Transformers\uB294 \uBAA8\uB378\uC5D0 \uB300\uD55C \uB370\uC774\uD130\uB97C 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\uD2B9\uC131 \uCD94\uCD9C\uAE30\uB294 \uBC30\uC5F4\uC5D0 `),se=t("code"),cm=n("0"),mm=n("(\uBB35\uC74C\uC73C\uB85C \uD574\uC11D)\uC744 \uCD94\uAC00\uD569\uB2C8\uB2E4."),Yp=o(),Ea=t("p"),ae=t("code"),om=n("AutoFeatureExtractor.from_pretrained()"),hm=n("\uB97C \uC0AC\uC6A9\uD558\uC5EC \uD2B9\uC131 \uCD94\uCD9C\uAE30\uB97C \uAC00\uC838\uC624\uC138\uC694:"),Fp=o(),f(Ia.$$.fragment),zp=o(),os=t("p"),um=n("\uC624\uB514\uC624 "),le=t("code"),jm=n("array"),bm=n("\uB97C \uD2B9\uC131 \uCD94\uCD9C\uAE30\uC5D0 \uC804\uB2EC\uD558\uC138\uC694. \uB610\uD55C, \uBC1C\uC0DD\uD560 \uC218 \uC788\uB294 \uC870\uC6A9\uD55C \uC624\uB958(silent errors)\uB97C \uB354 \uC798 \uB514\uBC84\uAE45\uD560 \uC218 \uC788\uB3C4\uB85D \uD2B9\uC131 \uCD94\uCD9C\uAE30\uC5D0 "),ne=t("code"),im=n("sampling_rate"),fm=n(" \uC778\uC218\uB97C \uCD94\uAC00\uD558\uB294 \uAC83\uC744 \uAD8C\uC7A5\uD569\uB2C8\uB2E4."),qp=o(),f(Ua.$$.fragment),Qp=o(),Ol=t("p"),dm=n("\uD1A0\uD06C\uB098\uC774\uC800\uC640 \uB9C8\uCC2C\uAC00\uC9C0\uB85C \uBC30\uCE58 \uB0B4\uC5D0\uC11C \uAC00\uBCC0\uC801\uC778 \uC2DC\uD000\uC2A4\uB97C \uCC98\uB9AC\uD558\uAE30 \uC704\uD574 \uD328\uB529 \uB610\uB294 \uC798\uB77C\uB0B4\uAE30\uB97C \uC801\uC6A9\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uC774 \uB450 \uAC1C\uC758 \uC624\uB514\uC624 \uC0D8\uD50C\uC758 \uC2DC\uD000\uC2A4 \uAE38\uC774\uB97C \uD655\uC778\uD574\uBCF4\uC138\uC694:"),Dp=o(),f(ka.$$.fragment),Pp=o(),Ll=t("p"),Jm=n("\uC624\uB514\uC624 \uC0D8\uD50C\uC758 \uAE38\uC774\uAC00 \uB3D9\uC77C\uD558\uB3C4\uB85D \uB370\uC774\uD130 \uC138\uD2B8\uB97C \uC804\uCC98\uB9AC\uD558\uB294 \uD568\uC218\uB97C \uB9CC\uB4DC\uC138\uC694. \uCD5C\uB300 \uC0D8\uD50C \uAE38\uC774\uB97C \uC9C0\uC815\uD558\uBA74 \uD2B9\uC131 \uCD94\uCD9C\uAE30\uAC00 \uD574\uB2F9 \uAE38\uC774\uC5D0 \uB9DE\uCDB0 \uC2DC\uD000\uC2A4\uB97C \uD328\uB529\uD558\uAC70\uB098 \uC798\uB77C\uB0C5\uB2C8\uB2E4:"),Sp=o(),f(Ca.$$.fragment),Hp=o(),Za=t("p"),ee=t("code"),$m=n("preprocess_function"),_m=n("\uC744 \uB370\uC774\uD130 \uC138\uD2B8\uC758 \uCC98\uC74C \uC608\uC2DC \uBA87 \uAC1C\uC5D0 \uC801\uC6A9\uD574\uBCF4\uC138\uC694:"),Op=o(),f(Ga.$$.fragment),Lp=o(),Kl=t("p"),Mm=n("\uC774\uC81C \uC0D8\uD50C \uAE38\uC774\uAC00 \uBAA8\uB450 \uAC19\uACE0 \uC9C0\uC815\uB41C \uCD5C\uB300 \uAE38\uC774\uC5D0 \uB9DE\uAC8C \uB418\uC5C8\uC2B5\uB2C8\uB2E4. \uB4DC\uB514\uC5B4 \uC804\uCC98\uB9AC\uB41C \uB370\uC774\uD130 \uC138\uD2B8\uB97C \uBAA8\uB378\uC5D0 \uC804\uB2EC\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4!"),Kp=o(),f(Va.$$.fragment),st=o(),ws=t("h2"),Fs=t("a"),pe=t("span"),f(Ba.$$.fragment),ym=o(),te=t("span"),wm=n("\uCEF4\uD4E8\uD130 \uBE44\uC804"),at=o(),zs=t("p"),vm=n("\uCEF4\uD4E8\uD130 \uBE44\uC804 \uC791\uC5C5\uC758 \uACBD\uC6B0, \uBAA8\uB378\uC5D0 \uB300\uD55C \uB370\uC774\uD130 \uC138\uD2B8\uB97C \uC900\uBE44\uD558\uAE30 \uC704\uD574 "),sn=t("a"),gm=n("\uC774\uBBF8\uC9C0 \uD504\uB85C\uC138\uC11C"),Tm=n(`\uAC00 \uD544\uC694\uD569\uB2C8\uB2E4.
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\uC774\uB7EC\uD55C \uB2E8\uACC4\uC5D0\uB294 \uD06C\uAE30 \uC870\uC815, \uC815\uADDC\uD654, \uC0C9\uC0C1 \uCC44\uB110 \uBCF4\uC815, \uC774\uBBF8\uC9C0\uC758 \uD150\uC11C \uBCC0\uD658 \uB4F1\uC774 \uD3EC\uD568\uB429\uB2C8\uB2E4.`),lt=o(),f(qs.$$.fragment),nt=o(),vs=t("p"),Wa=t("a"),Em=n("food101"),Im=n(` \uB370\uC774\uD130 \uC138\uD2B8\uB97C \uAC00\uC838\uC640\uC11C \uCEF4\uD4E8\uD130 \uBE44\uC804 \uB370\uC774\uD130 \uC138\uD2B8\uC5D0\uC11C \uC774\uBBF8\uC9C0 \uD504\uB85C\uC138\uC11C\uB97C \uC5B4\uB5BB\uAC8C \uC0AC\uC6A9\uD558\uB294\uC9C0 \uC54C\uC544\uBCF4\uC138\uC694.
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\uCC38\uACE0\uB85C \uD06C\uAE30 \uC870\uC815\uC5D0 \uD544\uC694\uD55C \uC774\uBBF8\uC9C0\uC758 \uD06C\uAE30 \uC694\uAD6C\uC0AC\uD56D\uC740 `),be=t("code"),Sm=n("image_processor"),Hm=n(`\uC5D0\uC11C \uAC00\uC838\uC62C \uC218 \uC788\uC2B5\uB2C8\uB2E4.
\uC77C\uBD80 \uBAA8\uB378\uC740 \uC815\uD655\uD55C \uB192\uC774\uC640 \uB108\uBE44\uB97C \uC694\uAD6C\uD558\uC9C0\uB9CC, \uC81C\uC77C \uC9E7\uC740 \uBCC0\uC758 \uAE38\uC774(`),ie=t("code"),Om=n("shortest_edge"),Lm=n(")\uB9CC \uC815\uC758\uB41C \uBAA8\uB378\uB3C4 \uC788\uC2B5\uB2C8\uB2E4."),jt=o(),f(Ha.$$.fragment),bt=o(),Oa=t("ol"),S=t("li"),Km=n("\uBAA8\uB378\uC740 \uC785\uB825\uC73C\uB85C "),ln=t("a"),fe=t("code"),so=n("pixel_values"),ao=n(`\uB97C \uBC1B\uC2B5\uB2C8\uB2E4.
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