import{S as vo,i as wo,s as $o,e as a,k as f,w as u,t as n,M as yo,c as r,d as s,m,a as o,x as h,h as p,b as c,G as t,g as i,y as d,q as v,o as w,B as $,v as _o}from"../chunks/vendor-hf-doc-builder.js";import{T as uo}from"../chunks/Tip-hf-doc-builder.js";import{Y as ho}from"../chunks/Youtube-hf-doc-builder.js";import{I as pe}from"../chunks/IconCopyLink-hf-doc-builder.js";import{C as M}from"../chunks/CodeBlock-hf-doc-builder.js";function bo(Se){let y,E,_,b,C;return{c(){y=a("p"),E=n("\uBA54\uBAA8\uB9AC \uC808\uC57D \uAE30\uC220\uC5D0 \uB300\uD55C \uC790\uC138\uD55C \uB0B4\uC6A9\uC740 \uC131\uB2A5 "),_=a("a"),b=n("\uAC00\uC774\uB4DC"),C=n("\uB97C \uCC38\uC870\uD558\uC138\uC694."),this.h()},l(g){y=r(g,"P",{});var T=o(y);E=p(T,"\uBA54\uBAA8\uB9AC \uC808\uC57D \uAE30\uC220\uC5D0 \uB300\uD55C \uC790\uC138\uD55C \uB0B4\uC6A9\uC740 \uC131\uB2A5 "),_=r(T,"A",{href:!0});var F=o(_);b=p(F,"\uAC00\uC774\uB4DC"),F.forEach(s),C=p(T,"\uB97C \uCC38\uC870\uD558\uC138\uC694."),T.forEach(s),this.h()},h(){c(_,"href","performance")},m(g,T){i(g,y,T),t(y,E),t(y,_),t(_,b),t(y,C)},d(g){g&&s(y)}}}function jo(Se){let y,E;return{c(){y=a("p"),E=n("\uC77C\uBC18\uC801\uC73C\uB85C \uD1A0\uD06C\uB098\uC774\uC800\uB294 \uD2B9\uC815 \uD1A0\uD06C\uB098\uC774\uC800\uC758 \uAE30\uBCF8 \uAC12\uC744 \uAE30\uC900\uC73C\uB85C \uC0AC\uC6A9\uC790\uC5D0 \uB300\uD55C \u2018attention_mask\u2019\uB97C \uB9CC\uB4ED\uB2C8\uB2E4.")},l(_){y=r(_,"P",{});var b=o(y);E=p(b,"\uC77C\uBC18\uC801\uC73C\uB85C \uD1A0\uD06C\uB098\uC774\uC800\uB294 \uD2B9\uC815 \uD1A0\uD06C\uB098\uC774\uC800\uC758 \uAE30\uBCF8 \uAC12\uC744 \uAE30\uC900\uC73C\uB85C \uC0AC\uC6A9\uC790\uC5D0 \uB300\uD55C \u2018attention_mask\u2019\uB97C \uB9CC\uB4ED\uB2C8\uB2E4."),b.forEach(s)},m(_,b){i(_,y,b),t(y,E)},d(_){_&&s(y)}}}function Mo(Se){let y,E,_,b,C,g,T,F,il,xs,De,fl,Ls,ie,Os,Xe,J,fe,ml,cl,me,ul,hl,ce,dl,vl,qs,ue,Ks,A,is,he,wl,de,$l,yl,_l,fs,ve,bl,He,jl,Ml,et,R,gl,we,El,Ul,st,I,S,ms,$e,kl,cs,Tl,tt,ze,Jl,lt,ye,at,D,Vl,Ye,Cl,Al,rt,Z,X,us,_e,Il,hs,Zl,ot,xe,Gl,nt,be,pt,Le,Bl,it,H,z,ds,Ql,Wl,Oe,vs,Pl,Nl,Fl,Y,ws,Rl,Sl,qe,$s,Dl,Xl,ft,x,mt,G,L,ys,je,Hl,_s,zl,ct,O,Yl,Me,xl,Ll,ut,Ke,k,Ol,bs,ql,Kl,ge,js,ea,sa,Ms,ta,la,ht,Ee,dt,es,B,aa,gs,ra,oa,Es,na,pa,vt,Ue,wt,Q,q,Us,ke,ia,ks,fa,$t,K,ma,Ts,ca,ua,yt,Te,_t,ss,ha,bt,Je,jt,W,ee,Js,Ve,da,Vs,va,Mt,ts,wa,gt,Ce,Et,ls,$a,Ut,Ae,kt,as,ya,Tt,Ie,Jt,P,se,Cs,Ze,_a,As,ba,Vt,j,ja,Is,Ma,ga,Zs,Ea,Ua,Gs,ka,Ta,Bs,Ja,Va,Qs,Ca,Aa,Ct,Ge,At,rs,Ia,It,Be,Zt,os,Za,Gt,Qe,Bt,te,Ga,Ws,Ba,Qa,Qt,le,Wt,We,Pt,ae,Wa,Ps,Pa,Na,Nt,re,Ns,Fa,Ra,Fs,Sa,Ft,N,oe,Rs,Pe,Da,Ss,Xa,Rt,V,Ha,Ds,za,Ya,Xs,xa,La,St,Ne,Dt;return g=new pe({}),ie=new ho({props:{id:"S2EEG3JIt2A"}}),ue=new ho({props:{id:"_PAli-V4wj0"}}),$e=new pe({}),ye=new M({props:{code:"VmFsdWVFcnJvciUzQSUyMENvbm5lY3Rpb24lMjBlcnJvciUyQyUyMGFuZCUyMHdlJTIwY2Fubm90JTIwZmluZCUyMHRoZSUyMHJlcXVlc3RlZCUyMGZpbGVzJTIwaW4lMjB0aGUlMjBjYWNoZWQlMjBwYXRoLiUwQVBsZWFzZSUyMHRyeSUyMGFnYWluJTIwb3IlMjBtYWtlJTIwc3VyZSUyMHlvdXIlMjBJbnRlcm5ldCUyMGNvbm5lY3Rpb24lMjBpcyUyMG9uLg==",highlighted:`ValueError: Connection error, <span class="hljs-built_in">and</span> we cannot <span class="hljs-keyword">find</span> the requested <span class="hljs-keyword">files</span> in the cached path.
Please <span class="hljs-keyword">try</span> again <span class="hljs-built_in">or</span> <span class="hljs-keyword">make</span> sure your Internet connection <span class="hljs-keyword">is</span> <span class="hljs-keyword">on</span>.`}}),_e=new pe({}),be=new M({props:{code:"Q1VEQSUyMG91dCUyMG9mJTIwbWVtb3J5LiUyMFRyaWVkJTIwdG8lMjBhbGxvY2F0ZSUyMDI1Ni4wMCUyME1pQiUyMChHUFUlMjAwJTNCJTIwMTEuMTclMjBHaUIlMjB0b3RhbCUyMGNhcGFjaXR5JTNCJTIwOS43MCUyMEdpQiUyMGFscmVhZHklMjBhbGxvY2F0ZWQlM0IlMjAxNzkuODElMjBNaUIlMjBmcmVlJTNCJTIwOS44NSUyMEdpQiUyMHJlc2VydmVkJTIwaW4lMjB0b3RhbCUyMGJ5JTIwUHlUb3JjaCk=",highlighted:'<span class="hljs-attribute">CUDA</span> out of memory. Tried to allocate <span class="hljs-number">256</span>.<span class="hljs-number">00</span> MiB (GPU <span class="hljs-number">0</span>; <span class="hljs-number">11</span>.<span class="hljs-number">17</span> GiB total capacity; <span class="hljs-number">9</span>.<span class="hljs-number">70</span> GiB already allocated; <span class="hljs-number">179</span>.<span class="hljs-number">81</span> MiB free; <span class="hljs-number">9</span>.<span class="hljs-number">85</span> GiB reserved in total by PyTorch)'}}),x=new uo({props:{$$slots:{default:[bo]},$$scope:{ctx:Se}}}),je=new pe({}),Ee=new M({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMFRGUHJlVHJhaW5lZE1vZGVsJTBBZnJvbSUyMHRlbnNvcmZsb3clMjBpbXBvcnQlMjBrZXJhcyUwQSUwQW1vZGVsLnNhdmVfd2VpZ2h0cyglMjJzb21lX2ZvbGRlciUyRnRmX21vZGVsLmg1JTIyKSUwQW1vZGVsJTIwJTNEJTIwVEZQcmVUcmFpbmVkTW9kZWwuZnJvbV9wcmV0cmFpbmVkKCUyMnNvbWVfZm9sZGVyJTIyKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> TFPreTrainedModel
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> tensorflow <span class="hljs-keyword">import</span> keras

<span class="hljs-meta">&gt;&gt;&gt; </span>model.save_weights(<span class="hljs-string">&quot;some_folder/tf_model.h5&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = TFPreTrainedModel.from_pretrained(<span class="hljs-string">&quot;some_folder&quot;</span>)`}}),Ue=new M({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMFRGUHJlVHJhaW5lZE1vZGVsJTBBJTBBbW9kZWwuc2F2ZV9wcmV0cmFpbmVkKCUyMnBhdGhfdG8lMkZtb2RlbCUyMiklMEFtb2RlbCUyMCUzRCUyMFRGUHJlVHJhaW5lZE1vZGVsLmZyb21fcHJldHJhaW5lZCglMjJwYXRoX3RvJTJGbW9kZWwlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> TFPreTrainedModel

<span class="hljs-meta">&gt;&gt;&gt; </span>model.save_pretrained(<span class="hljs-string">&quot;path_to/model&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = TFPreTrainedModel.from_pretrained(<span class="hljs-string">&quot;path_to/model&quot;</span>)`}}),ke=new pe({}),Te=new M({props:{code:"SW1wb3J0RXJyb3IlM0ElMjBjYW5ub3QlMjBpbXBvcnQlMjBuYW1lJTIwJ0ltYWdlR1BUSW1hZ2VQcm9jZXNzb3InJTIwZnJvbSUyMCd0cmFuc2Zvcm1lcnMnJTIwKHVua25vd24lMjBsb2NhdGlvbik=",highlighted:'ImportError: cannot <span class="hljs-keyword">import</span> <span class="hljs-type">name</span> <span class="hljs-string">&#x27;ImageGPTImageProcessor&#x27;</span> <span class="hljs-keyword">from</span> <span class="hljs-string">&#x27;transformers&#x27;</span> (<span class="hljs-type">unknown</span> <span class="hljs-keyword">location</span>)'}}),Je=new M({props:{code:"cGlwJTIwaW5zdGFsbCUyMHRyYW5zZm9ybWVycyUyMC0tdXBncmFkZQ==",highlighted:"pip install transformers --upgrade"}}),Ve=new pe({}),Ce=new M({props:{code:"UnVudGltZUVycm9yJTNBJTIwQ1VEQSUyMGVycm9yJTNBJTIwZGV2aWNlLXNpZGUlMjBhc3NlcnQlMjB0cmlnZ2VyZWQ=",highlighted:'RuntimeError: CUDA <span class="hljs-literal">error</span>: device-<span class="hljs-literal">side</span> <span class="hljs-keyword">assert</span> triggered'}}),Ae=new M({props:{code:"aW1wb3J0JTIwb3MlMEElMEFvcy5lbnZpcm9uJTVCJTIyQ1VEQV9WSVNJQkxFX0RFVklDRVMlMjIlNUQlMjAlM0QlMjAlMjIlMjI=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> os

<span class="hljs-meta">&gt;&gt;&gt; </span>os.environ[<span class="hljs-string">&quot;CUDA_VISIBLE_DEVICES&quot;</span>] = <span class="hljs-string">&quot;&quot;</span>`}}),Ie=new M({props:{code:"aW1wb3J0JTIwb3MlMEElMEFvcy5lbnZpcm9uJTVCJTIyQ1VEQV9MQVVOQ0hfQkxPQ0tJTkclMjIlNUQlMjAlM0QlMjAlMjIxJTIy",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> os

<span class="hljs-meta">&gt;&gt;&gt; </span>os.environ[<span class="hljs-string">&quot;CUDA_LAUNCH_BLOCKING&quot;</span>] = <span class="hljs-string">&quot;1&quot;</span>`}}),Ze=new pe({}),Ge=new M({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9Nb2RlbEZvclNlcXVlbmNlQ2xhc3NpZmljYXRpb24lMEFpbXBvcnQlMjB0b3JjaCUwQSUwQW1vZGVsJTIwJTNEJTIwQXV0b01vZGVsRm9yU2VxdWVuY2VDbGFzc2lmaWNhdGlvbi5mcm9tX3ByZXRyYWluZWQoJTIyYmVydC1iYXNlLXVuY2FzZWQlMjIpJTBBbW9kZWwuY29uZmlnLnBhZF90b2tlbl9pZA==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModelForSequenceClassification
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> torch

<span class="hljs-meta">&gt;&gt;&gt; </span>model = AutoModelForSequenceClassification.from_pretrained(<span class="hljs-string">&quot;bert-base-uncased&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model.config.pad_token_id
<span class="hljs-number">0</span>`}}),Be=new M({props:{code:"aW5wdXRfaWRzJTIwJTNEJTIwdG9yY2gudGVuc29yKCU1QiU1Qjc1OTIlMkMlMjAyMDU3JTJDJTIwMjA5NyUyQyUyMDIzOTMlMkMlMjA5NjExJTJDJTIwMjExNSU1RCUyQyUyMCU1Qjc1OTIlMkMlMjAwJTJDJTIwMCUyQyUyMDAlMkMlMjAwJTJDJTIwMCU1RCU1RCklMEFvdXRwdXQlMjAlM0QlMjBtb2RlbChpbnB1dF9pZHMpJTBBcHJpbnQob3V0cHV0LmxvZ2l0cyk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>input_ids = torch.tensor([[<span class="hljs-number">7592</span>, <span class="hljs-number">2057</span>, <span class="hljs-number">2097</span>, <span class="hljs-number">2393</span>, <span class="hljs-number">9611</span>, <span class="hljs-number">2115</span>], [<span class="hljs-number">7592</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-meta">&gt;&gt;&gt; </span>output = model(input_ids)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(output.logits)
tensor([[ <span class="hljs-number">0.0082</span>, -<span class="hljs-number">0.2307</span>],
        [ <span class="hljs-number">0.1317</span>, -<span class="hljs-number">0.1683</span>]], grad_fn=&lt;AddmmBackward0&gt;)`}}),Qe=new M({props:{code:"aW5wdXRfaWRzJTIwJTNEJTIwdG9yY2gudGVuc29yKCU1QiU1Qjc1OTIlNUQlNUQpJTBBb3V0cHV0JTIwJTNEJTIwbW9kZWwoaW5wdXRfaWRzKSUwQXByaW50KG91dHB1dC5sb2dpdHMp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>input_ids = torch.tensor([[<span class="hljs-number">7592</span>]])
<span class="hljs-meta">&gt;&gt;&gt; </span>output = model(input_ids)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(output.logits)
tensor([[-<span class="hljs-number">0.1008</span>, -<span class="hljs-number">0.4061</span>]], grad_fn=&lt;AddmmBackward0&gt;)`}}),le=new uo({props:{$$slots:{default:[jo]},$$scope:{ctx:Se}}}),We=new M({props:{code:"YXR0ZW50aW9uX21hc2slMjAlM0QlMjB0b3JjaC50ZW5zb3IoJTVCJTVCMSUyQyUyMDElMkMlMjAxJTJDJTIwMSUyQyUyMDElMkMlMjAxJTVEJTJDJTIwJTVCMSUyQyUyMDAlMkMlMjAwJTJDJTIwMCUyQyUyMDAlMkMlMjAwJTVEJTVEKSUwQW91dHB1dCUyMCUzRCUyMG1vZGVsKGlucHV0X2lkcyUyQyUyMGF0dGVudGlvbl9tYXNrJTNEYXR0ZW50aW9uX21hc2spJTBBcHJpbnQob3V0cHV0LmxvZ2l0cyk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>attention_mask = torch.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">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-meta">&gt;&gt;&gt; </span>output = model(input_ids, attention_mask=attention_mask)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(output.logits)
tensor([[ <span class="hljs-number">0.0082</span>, -<span class="hljs-number">0.2307</span>],
        [-<span class="hljs-number">0.1008</span>, -<span class="hljs-number">0.4061</span>]], grad_fn=&lt;AddmmBackward0&gt;)`}}),Pe=new pe({}),Ne=new M({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMEF1dG9Qcm9jZXNzb3IlMkMlMjBBdXRvTW9kZWxGb3JRdWVzdGlvbkFuc3dlcmluZyUwQSUwQXByb2Nlc3NvciUyMCUzRCUyMEF1dG9Qcm9jZXNzb3IuZnJvbV9wcmV0cmFpbmVkKCUyMmdwdDItbWVkaXVtJTIyKSUwQW1vZGVsJTIwJTNEJTIwQXV0b01vZGVsRm9yUXVlc3Rpb25BbnN3ZXJpbmcuZnJvbV9wcmV0cmFpbmVkKCUyMmdwdDItbWVkaXVtJTIyKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoProcessor, AutoModelForQuestionAnswering

<span class="hljs-meta">&gt;&gt;&gt; </span>processor = AutoProcessor.from_pretrained(<span class="hljs-string">&quot;gpt2-medium&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = AutoModelForQuestionAnswering.from_pretrained(<span class="hljs-string">&quot;gpt2-medium&quot;</span>)
ValueError: Unrecognized configuration <span class="hljs-keyword">class</span> &lt;<span class="hljs-keyword">class</span> <span class="hljs-string">&#x27;transformers.models.gpt2.configuration_gpt2.GPT2Config&#x27;</span>&gt; <span class="hljs-keyword">for</span> this kind of AutoModel: AutoModelForQuestionAnswering.
Model <span class="hljs-built_in">type</span> should be one of AlbertConfig, BartConfig, BertConfig, BigBirdConfig, BigBirdPegasusConfig, BloomConfig, ...`}}),{c(){y=a("meta"),E=f(),_=a("h1"),b=a("a"),C=a("span"),u(g.$$.fragment),T=f(),F=a("span"),il=n("\uBB38\uC81C \uD574\uACB0"),xs=f(),De=a("p"),fl=n("\uB54C\uB54C\uB85C \uC624\uB958\uAC00 \uBC1C\uC0DD\uD560 \uC218 \uC788\uC9C0\uB9CC, \uC800\uD76C\uAC00 \uB3C4\uC640\uB4DC\uB9AC\uACA0\uC2B5\uB2C8\uB2E4! \uC774 \uAC00\uC774\uB4DC\uB294 \uD604\uC7AC\uAE4C\uC9C0 \uD655\uC778\uB41C \uAC00\uC7A5 \uC77C\uBC18\uC801\uC778 \uBB38\uC81C \uBA87 \uAC00\uC9C0\uC640 \uADF8\uAC83\uB4E4\uC744 \uD574\uACB0\uD558\uB294 \uBC29\uBC95\uC5D0 \uB300\uD574 \uB2E4\uB8F9\uB2C8\uB2E4. \uADF8\uB7EC\uB098 \uC774 \uAC00\uC774\uB4DC\uB294 \uBAA8\uB4E0 \u{1F917} Transformers \uBB38\uC81C\uB97C \uD3EC\uAD04\uC801\uC73C\uB85C \uB2E4\uB8E8\uACE0 \uC788\uC9C0 \uC54A\uC2B5\uB2C8\uB2E4. \uBB38\uC81C \uD574\uACB0\uC5D0 \uB354 \uB9CE\uC740 \uB3C4\uC6C0\uC744 \uBC1B\uC73C\uB824\uBA74 \uB2E4\uC74C\uC744 \uC2DC\uB3C4\uD574\uBCF4\uC138\uC694:"),Ls=f(),u(ie.$$.fragment),Os=f(),Xe=a("ol"),J=a("li"),fe=a("a"),ml=n("\uD3EC\uB7FC"),cl=n("\uC5D0\uC11C \uB3C4\uC6C0\uC744 \uC694\uCCAD\uD558\uC138\uC694. 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masked)"),Vt=f(),j=a("p"),ja=n("\uACBD\uC6B0\uC5D0 \uB530\uB77C "),Is=a("code"),Ma=n("input_ids"),ga=n("\uC5D0 \uD328\uB529 \uD1A0\uD070\uC774 \uD3EC\uD568\uB41C \uACBD\uC6B0 "),Zs=a("code"),Ea=n("hidden_state"),Ua=n(" \uCD9C\uB825\uC774 \uC62C\uBC14\uB974\uC9C0 \uC54A\uC744 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uB370\uBAA8\uB97C \uC704\uD574 \uBAA8\uB378\uACFC \uD1A0\uD06C\uB098\uC774\uC800\uB97C \uAC00\uC838\uC624\uC138\uC694. \uBAA8\uB378\uC758 "),Gs=a("code"),ka=n("pad_token_id"),Ta=n("\uC5D0 \uC561\uC138\uC2A4\uD558\uC5EC \uD574\uB2F9 \uAC12\uC744 \uD655\uC778\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uC77C\uBD80 \uBAA8\uB378\uC758 \uACBD\uC6B0 "),Bs=a("code"),Ja=n("pad_token_id"),Va=n("\uAC00 "),Qs=a("code"),Ca=n("None"),Aa=n("\uC77C \uC218 \uC788\uC9C0\uB9CC \uC5B8\uC81C\uB4E0\uC9C0 \uC218\uB3D9\uC73C\uB85C \uC124\uC815\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4."),Ct=f(),u(Ge.$$.fragment),At=f(),rs=a("p"),Ia=n("\uB2E4\uC74C \uC608\uC81C\uB294 \uD328\uB529 \uD1A0\uD070\uC744 \uB9C8\uC2A4\uD0B9\uD558\uC9C0 \uC54A\uC740 \uCD9C\uB825\uC744 \uBCF4\uC5EC\uC90D\uB2C8\uB2E4:"),It=f(),u(Be.$$.fragment),Zt=f(),os=a("p"),Za=n("\uB2E4\uC74C\uC740 \uB450 \uBC88\uC9F8 \uC2DC\uD000\uC2A4\uC758 \uC2E4\uC81C \uCD9C\uB825\uC785\uB2C8\uB2E4:"),Gt=f(),u(Qe.$$.fragment),Bt=f(),te=a("p"),Ga=n("\uB300\uBD80\uBD84\uC758 \uACBD\uC6B0 \uBAA8\uB378\uC5D0 "),Ws=a("code"),Ba=n("attention_mask"),Qa=n("\uB97C \uC81C\uACF5\uD558\uC5EC \uD328\uB529 \uD1A0\uD070\uC744 \uBB34\uC2DC\uD574\uC57C \uC774\uB7EC\uD55C \uC870\uC6A9\uD55C \uC624\uB958\uB97C \uBC29\uC9C0\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uC774\uC81C \uB450 \uBC88\uC9F8 \uC2DC\uD000\uC2A4\uC758 \uCD9C\uB825\uC774 \uC2E4\uC81C \uCD9C\uB825\uACFC \uC77C\uCE58\uD569\uB2C8\uB2E4:"),Qt=f(),u(le.$$.fragment),Wt=f(),u(We.$$.fragment),Pt=f(),ae=a("p"),Wa=n("\u{1F917} Transformers\uB294 \uD328\uB529 \uD1A0\uD070\uC774 \uC81C\uACF5\uB41C \uACBD\uC6B0 \uD328\uB529 \uD1A0\uD070\uC744 \uB9C8\uC2A4\uD0B9\uD558\uAE30 \uC704\uD55C "),Ps=a("code"),Pa=n("attention_mask"),Na=n("\uB97C \uC790\uB3D9\uC73C\uB85C \uC0DD\uC131\uD558\uC9C0 \uC54A\uC2B5\uB2C8\uB2E4. \uADF8 \uC774\uC720\uB294 \uB2E4\uC74C\uACFC \uAC19\uC2B5\uB2C8\uB2E4:"),Nt=f(),re=a("ul"),Ns=a("li"),Fa=n("\uC77C\uBD80 \uBAA8\uB378\uC5D0\uB294 \uD328\uB529 \uD1A0\uD070\uC774 \uC5C6\uC2B5\uB2C8\uB2E4."),Ra=f(),Fs=a("li"),Sa=n("\uC77C\uBD80 \uC0AC\uC6A9 \uC0AC\uB840\uC758 \uACBD\uC6B0 \uC0AC\uC6A9\uC790\uAC00 \uBAA8\uB378\uC774 \uD328\uB529 \uD1A0\uD070\uC744 \uAD00\uB9AC\uD558\uAE30\uB97C \uC6D0\uD569\uB2C8\uB2E4."),Ft=f(),N=a("h2"),oe=a("a"),Rs=a("span"),u(Pe.$$.fragment),Da=f(),Ss=a("span"),Xa=n("ValueError: \uC774 \uC720\uD615\uC758 AutoModel\uC5D0 \uB300\uD574 \uC778\uC2DD\uD560 \uC218 \uC5C6\uB294 XYZ \uAD6C\uC131 \uD074\uB798\uC2A4(ValueError: Unrecognized configuration class XYZ for this kind of AutoModel)"),Rt=f(),V=a("p"),Ha=n("\uC77C\uBC18\uC801\uC73C\uB85C, \uC0AC\uC804 \uD559\uC2B5\uB41C \uBAA8\uB378\uC758 \uC778\uC2A4\uD134\uC2A4\uB97C \uAC00\uC838\uC624\uAE30 \uC704\uD574 "),Ds=a("code"),za=n("AutoModel"),Ya=n(` \uD074\uB798\uC2A4\uB97C \uC0AC\uC6A9\uD558\uB294 \uAC83\uC774 \uC88B\uC2B5\uB2C8\uB2E4.
\uC774 \uD074\uB798\uC2A4\uB294 \uAD6C\uC131\uC5D0 \uB530\uB77C \uC8FC\uC5B4\uC9C4 \uCCB4\uD06C\uD3EC\uC778\uD2B8\uC5D0\uC11C \uC62C\uBC14\uB978 \uC544\uD0A4\uD14D\uCC98\uB97C \uC790\uB3D9\uC73C\uB85C \uCD94\uB860\uD558\uACE0 \uAC00\uC838\uC62C \uC218 \uC788\uC2B5\uB2C8\uB2E4.
\uBAA8\uB378\uC744 \uCCB4\uD06C\uD3EC\uC778\uD2B8\uC5D0\uC11C \uAC00\uC838\uC62C \uB54C \uC774 `),Xs=a("code"),xa=n("ValueError"),La=n(`\uAC00 \uBC1C\uC0DD\uD558\uBA74, \uC774\uB294 Auto \uD074\uB798\uC2A4\uAC00 \uC8FC\uC5B4\uC9C4 \uCCB4\uD06C\uD3EC\uC778\uD2B8\uC758 \uAD6C\uC131\uC5D0\uC11C
\uAC00\uC838\uC624\uB824\uB294 \uBAA8\uB378 \uC720\uD615\uACFC \uB9E4\uD551\uC744 \uCC3E\uC744 \uC218 \uC5C6\uB2E4\uB294 \uAC83\uC744 \uC758\uBBF8\uD569\uB2C8\uB2E4. \uAC00\uC7A5 \uD754\uD558\uAC8C \uBC1C\uC0DD\uD558\uB294 \uACBD\uC6B0\uB294
\uCCB4\uD06C\uD3EC\uC778\uD2B8\uAC00 \uC8FC\uC5B4\uC9C4 \uD0DC\uC2A4\uD06C\uB97C \uC9C0\uC6D0\uD558\uC9C0 \uC54A\uC744 \uB54C\uC785\uB2C8\uB2E4.
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