import{S as sn,i as on,s as rn,e as n,k as m,w as c,t as o,M as nn,c as a,d as t,m as f,a as p,x as d,h as r,b as u,G as l,g as i,y as h,q as b,o as y,B as N,v as an}from"../chunks/vendor-hf-doc-builder.js";import{T as pn}from"../chunks/Tip-hf-doc-builder.js";import{I as lt}from"../chunks/IconCopyLink-hf-doc-builder.js";import{C as T}from"../chunks/CodeBlock-hf-doc-builder.js";function mn(Ct){let M,g,_,$;return{c(){M=n("p"),g=n("code"),_=o("tranformers.onnx"),$=o("\uB294 \uB354 \uC774\uC0C1 \uC720\uC9C0\uB418\uC9C0 \uC54A\uC2B5\uB2C8\uB2E4. \uC704\uC5D0\uC11C \uC124\uBA85\uD55C \uB300\uB85C \u{1F917} Optimum\uC744 \uC0AC\uC6A9\uD558\uC5EC \uBAA8\uB378\uC744 \uB0B4\uBCF4\uB0B4\uC138\uC694. \uC774 \uC139\uC158\uC740 \uD5A5\uD6C4 \uBC84\uC804\uC5D0\uC11C \uC81C\uAC70\uB420 \uC608\uC815\uC785\uB2C8\uB2E4.")},l(E){M=a(E,"P",{});var J=p(M);g=a(J,"CODE",{});var Ce=p(g);_=r(Ce,"tranformers.onnx"),Ce.forEach(t),$=r(J,"\uB294 \uB354 \uC774\uC0C1 \uC720\uC9C0\uB418\uC9C0 \uC54A\uC2B5\uB2C8\uB2E4. \uC704\uC5D0\uC11C \uC124\uBA85\uD55C \uB300\uB85C \u{1F917} Optimum\uC744 \uC0AC\uC6A9\uD558\uC5EC \uBAA8\uB378\uC744 \uB0B4\uBCF4\uB0B4\uC138\uC694. \uC774 \uC139\uC158\uC740 \uD5A5\uD6C4 \uBC84\uC804\uC5D0\uC11C \uC81C\uAC70\uB420 \uC608\uC815\uC785\uB2C8\uB2E4."),J.forEach(t)},m(E,J){i(E,M,J),l(M,g),l(g,_),l(M,$)},d(E){E&&t(M)}}}function fn(Ct){let M,g,_,$,E,J,Ce,st,Ql,Bt,Be,Yl,Vt,B,Pl,ot,ql,Ll,It,V,Dl,Ve,Kl,es,Ft,Z,I,rt,re,ts,nt,ls,zt,k,ne,ss,os,at,rs,ns,At,Ie,as,St,Fe,ps,Ht,x,F,ae,is,ms,pe,fs,us,cs,O,ds,z,pt,hs,bs,ys,it,Ns,ws,Ms,A,ie,vs,Ts,mt,_s,Js,Qt,ze,$s,Yt,S,Xs,me,Es,gs,Pt,Ae,xs,qt,H,ft,Us,js,Se,ut,Zs,ks,Lt,R,Q,ct,fe,Os,dt,Rs,Dt,He,Ws,Kt,ue,el,Y,Gs,ce,Cs,Bs,tl,de,ll,P,Vs,ht,Is,Fs,sl,he,ol,q,zs,bt,As,Ss,rl,be,nl,w,Hs,yt,Qs,Ys,Nt,Ps,qs,wt,Ls,Ds,Mt,Ks,eo,ye,to,lo,vt,so,oo,al,Ne,pl,X,ro,Tt,no,ao,we,po,io,Me,mo,fo,il,ve,ml,L,uo,Te,co,ho,fl,_e,ul,W,D,_t,Je,bo,Qe,Jt,yo,No,cl,K,wo,$t,Mo,vo,dl,$e,hl,G,ee,Xt,Xe,To,Et,_o,bl,U,Jo,Ee,gt,$o,Xo,ge,Eo,go,yl,C,te,xt,xe,xo,Ye,Ut,Uo,jo,Nl,le,wl,Pe,Zo,Ml,Ue,vl,je,jt,ko,Oo,Tl,Ze,_l,j,Ro,Zt,Wo,Go,kt,Co,Bo,Jl,ke,$l,se,Vo,Ot,Io,Fo,Xl,Oe,El,qe,zo,gl,Re,xl,Le,Ao,Ul,We,jl;return J=new lt({}),re=new lt({}),fe=new lt({}),ue=new T({props:{code:"cGlwJTIwaW5zdGFsbCUyMG9wdGltdW0lNUJleHBvcnRlcnMlNUQ=",highlighted:"pip install optimum[exporters]"}}),de=new T({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1oZWxw",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --<span class="hljs-built_in">help</span>'}}),he=new T({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1tb2RlbCUyMGRpc3RpbGJlcnQtYmFzZS11bmNhc2VkLWRpc3RpbGxlZC1zcXVhZCUyMGRpc3RpbGJlcnRfYmFzZV91bmNhc2VkX3NxdWFkX29ubnglMkY=",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --model distilbert-base-uncased-distilled-squad distilbert_base_uncased_squad_onnx/'}}),be=new T({props:{code:"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",highlighted:`Validating ONNX model distilbert_base_uncased_squad_onnx/model.onnx...
	-[\u2713] ONNX model output names match reference model (start_logits, end_logits)
	- Validating ONNX Model output <span class="hljs-string">&quot;start_logits&quot;</span>:
		-[\u2713] (2, 16) matches (2, 16)
		-[\u2713] all values close (atol: 0.0001)
	- Validating ONNX Model output <span class="hljs-string">&quot;end_logits&quot;</span>:
		-[\u2713] (2, 16) matches (2, 16)
		-[\u2713] all values close (atol: 0.0001)
The ONNX <span class="hljs-built_in">export</span> succeeded and the exported model was saved at: distilbert_base_uncased_squad_onnx`}}),Ne=new T({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1tb2RlbCUyMGxvY2FsX3BhdGglMjAtLXRhc2slMjBxdWVzdGlvbi1hbnN3ZXJpbmclMjBkaXN0aWxiZXJ0X2Jhc2VfdW5jYXNlZF9zcXVhZF9vbm54JTJG",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --model local_path --task question-answering distilbert_base_uncased_squad_onnx/'}}),ve=new T({props:{code:"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",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><span class="hljs-keyword">from</span> optimum.onnxruntime <span class="hljs-keyword">import</span> ORTModelForQuestionAnswering

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;distilbert_base_uncased_squad_onnx&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>model = ORTModelForQuestionAnswering.from_pretrained(<span class="hljs-string">&quot;distilbert_base_uncased_squad_onnx&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>inputs = tokenizer(<span class="hljs-string">&quot;What am I using?&quot;</span>, <span class="hljs-string">&quot;Using DistilBERT with ONNX Runtime!&quot;</span>, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>outputs = model(**inputs)`}}),_e=new T({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1tb2RlbCUyMGtlcmFzLWlvJTJGdHJhbnNmb3JtZXJzLXFhJTIwZGlzdGlsYmVydF9iYXNlX2Nhc2VkX3NxdWFkX29ubnglMkY=",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --model keras-io/transformers-qa distilbert_base_cased_squad_onnx/'}}),Je=new lt({}),$e=new T({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> optimum.onnxruntime <span class="hljs-keyword">import</span> ORTModelForSequenceClassification
<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>model_checkpoint = <span class="hljs-string">&quot;distilbert_base_uncased_squad&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>save_directory = <span class="hljs-string">&quot;onnx/&quot;</span>

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Load a model from transformers and export it to ONNX</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>ort_model = ORTModelForSequenceClassification.from_pretrained(model_checkpoint, export=<span class="hljs-literal">True</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Save the onnx model and tokenizer</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>ort_model.save_pretrained(save_directory)
<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer.save_pretrained(save_directory)`}}),Xe=new lt({}),xe=new lt({}),le=new pn({props:{warning:!0,$$slots:{default:[mn]},$$scope:{ctx:Ct}}}),Ue=new T({props:{code:"cGlwJTIwaW5zdGFsbCUyMHRyYW5zZm9ybWVycyU1Qm9ubnglNUQ=",highlighted:"pip install transformers[onnx]"}}),Ze=new T({props:{code:"cHl0aG9uJTIwLW0lMjB0cmFuc2Zvcm1lcnMub25ueCUyMC0tbW9kZWwlM0RkaXN0aWxiZXJ0LWJhc2UtdW5jYXNlZCUyMG9ubnglMkY=",highlighted:"python -m transformers.onnx --model=distilbert-base-uncased onnx/"}}),ke=new T({props:{code:"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",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><span class="hljs-keyword">from</span> onnxruntime <span class="hljs-keyword">import</span> InferenceSession

<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;distilbert-base-uncased&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>session = InferenceSession(<span class="hljs-string">&quot;onnx/model.onnx&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># ONNX Runtime expects NumPy arrays as input</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>inputs = tokenizer(<span class="hljs-string">&quot;Using DistilBERT with ONNX Runtime!&quot;</span>, return_tensors=<span class="hljs-string">&quot;np&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>outputs = session.run(output_names=[<span class="hljs-string">&quot;last_hidden_state&quot;</span>], input_feed=<span class="hljs-built_in">dict</span>(inputs))`}}),Oe=new T({props:{code:"ZnJvbSUyMHRyYW5zZm9ybWVycy5tb2RlbHMuZGlzdGlsYmVydCUyMGltcG9ydCUyMERpc3RpbEJlcnRDb25maWclMkMlMjBEaXN0aWxCZXJ0T25ueENvbmZpZyUwQSUwQWNvbmZpZyUyMCUzRCUyMERpc3RpbEJlcnRDb25maWcoKSUwQW9ubnhfY29uZmlnJTIwJTNEJTIwRGlzdGlsQmVydE9ubnhDb25maWcoY29uZmlnKSUwQXByaW50KGxpc3Qob25ueF9jb25maWcub3V0cHV0cy5rZXlzKCkpKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers.models.distilbert <span class="hljs-keyword">import</span> DistilBertConfig, DistilBertOnnxConfig

<span class="hljs-meta">&gt;&gt;&gt; </span>config = DistilBertConfig()
<span class="hljs-meta">&gt;&gt;&gt; </span>onnx_config = DistilBertOnnxConfig(config)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(<span class="hljs-built_in">list</span>(onnx_config.outputs.keys()))
[<span class="hljs-string">&quot;last_hidden_state&quot;</span>]`}}),Re=new T({props:{code:"cHl0aG9uJTIwLW0lMjB0cmFuc2Zvcm1lcnMub25ueCUyMC0tbW9kZWwlM0RrZXJhcy1pbyUyRnRyYW5zZm9ybWVycy1xYSUyMG9ubnglMkY=",highlighted:"python -m transformers.onnx --model=keras-io/transformers-qa onnx/"}}),We=new T({props:{code:"cHl0aG9uJTIwLW0lMjB0cmFuc2Zvcm1lcnMub25ueCUyMC0tbW9kZWwlM0Rsb2NhbC1wdC1jaGVja3BvaW50JTIwb25ueCUyRg==",highlighted:"python -m transformers.onnx --model=local-pt-checkpoint onnx/"}}),{c(){M=n("meta"),g=m(),_=n("h1"),$=n("a"),E=n("span"),c(J.$$.fragment),Ce=m(),st=n("span"),Ql=o("ONNX\uB85C \uB0B4\uBCF4\uB0B4\uAE30"),Bt=m(),Be=n("p"),Yl=o("\u{1F917} Transformers \uBAA8\uB378\uC744 \uC81C\uD488 \uD658\uACBD\uC5D0\uC11C \uBC30\uD3EC\uD558\uAE30 \uC704\uD574\uC11C\uB294 \uBAA8\uB378\uC744 \uC9C1\uB82C\uD654\uB41C \uD615\uC2DD\uC73C\uB85C \uB0B4\uBCF4\uB0B4\uACE0 \uD2B9\uC815 \uB7F0\uD0C0\uC784\uACFC \uD558\uB4DC\uC6E8\uC5B4\uC5D0\uC11C \uB85C\uB4DC\uD558\uACE0 \uC2E4\uD589\uD560 \uC218 \uC788\uC73C\uBA74 \uC720\uC6A9\uD569\uB2C8\uB2E4."),Vt=m(),B=n("p"),Pl=o("\u{1F917} Optimum\uC740 Transformers\uC758 \uD655\uC7A5\uC73C\uB85C, PyTorch \uB610\uB294 TensorFlow\uC5D0\uC11C \uBAA8\uB378\uC744 ONNX\uC640 TFLite\uC640 \uAC19\uC740 \uC9C1\uB82C\uD654\uB41C \uD615\uC2DD\uC73C\uB85C \uB0B4\uBCF4\uB0BC \uC218 \uC788\uB3C4\uB85D \uD558\uB294 "),ot=n("code"),ql=o("exporters"),Ll=o(" \uBAA8\uB4C8\uC744 \uD1B5\uD574 \uC81C\uACF5\uB429\uB2C8\uB2E4. \u{1F917} Optimum\uC740 \uB610\uD55C \uC131\uB2A5 \uCD5C\uC801\uD654 \uB3C4\uAD6C \uC138\uD2B8\uB97C \uC81C\uACF5\uD558\uC5EC \uD2B9\uC815 \uD558\uB4DC\uC6E8\uC5B4\uC5D0\uC11C \uBAA8\uB378\uC744 \uD6C8\uB828\uD558\uACE0 \uC2E4\uD589\uD560 \uB54C \uCD5C\uB300 \uD6A8\uC728\uC131\uC744 \uB2EC\uC131\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4."),It=m(),V=n("p"),Dl=o("\uC774 \uC548\uB0B4\uC11C\uB294 \u{1F917} Optimum\uC744 \uC0AC\uC6A9\uD558\uC5EC \u{1F917} Transformers \uBAA8\uB378\uC744 ONNX\uB85C \uB0B4\uBCF4\uB0B4\uB294 \uBC29\uBC95\uC744 \uBCF4\uC5EC\uC90D\uB2C8\uB2E4. TFLite\uB85C \uBAA8\uB378\uC744 \uB0B4\uBCF4\uB0B4\uB294 \uC548\uB0B4\uC11C\uB294 "),Ve=n("a"),Kl=o("TFLite\uB85C \uB0B4\uBCF4\uB0B4\uAE30 \uD398\uC774\uC9C0"),es=o("\uB97C \uCC38\uC870\uD558\uC138\uC694."),Ft=m(),Z=n("h2"),I=n("a"),rt=n("span"),c(re.$$.fragment),ts=m(),nt=n("span"),ls=o("ONNX\uB85C \uB0B4\uBCF4\uB0B4\uAE30"),zt=m(),k=n("p"),ne=n("a"),ss=o("ONNX (Open Neural Network eXchange)"),os=o("\uB294 PyTorch\uC640 TensorFlow\uB97C \uD3EC\uD568\uD55C \uB2E4\uC591\uD55C \uD504\uB808\uC784\uC6CC\uD06C\uC5D0\uC11C \uC2EC\uCE35 \uD559\uC2B5 \uBAA8\uB378\uC744 \uB098\uD0C0\uB0B4\uB294 \uB370 \uC0AC\uC6A9\uB418\uB294 \uACF5\uD1B5 \uC5F0\uC0B0\uC790 \uC138\uD2B8\uC640 \uACF5\uD1B5 \uD30C\uC77C \uD615\uC2DD\uC744 \uC815\uC758\uD558\uB294 \uC624\uD508 \uD45C\uC900\uC785\uB2C8\uB2E4. \uBAA8\uB378\uC774 ONNX \uD615\uC2DD\uC73C\uB85C \uB0B4\uBCF4\uB0B4\uC9C0\uBA74 \uC774\uB7EC\uD55C \uC5F0\uC0B0\uC790\uB97C \uC0AC\uC6A9\uD558\uC5EC \uC2E0\uACBD\uB9DD\uC744 \uD1B5\uD574 \uB370\uC774\uD130\uAC00 \uD750\uB974\uB294 \uD750\uB984\uC744 \uB098\uD0C0\uB0B4\uB294 \uACC4\uC0B0 \uADF8\uB798\uD504(\uC77C\uBC18\uC801\uC73C\uB85C "),at=n("em"),rs=o("\uC911\uAC04 \uD45C\uD604"),ns=o("\uC774\uB77C\uACE0 \uD568)\uAC00 \uAD6C\uC131\uB429\uB2C8\uB2E4."),At=m(),Ie=n("p"),as=o("\uD45C\uC900\uD654\uB41C \uC5F0\uC0B0\uC790\uC640 \uB370\uC774\uD130 \uC720\uD615\uC744 \uAC00\uC9C4 \uADF8\uB798\uD504\uB97C \uB178\uCD9C\uD568\uC73C\uB85C\uC368, ONNX\uB294 \uD504\uB808\uC784\uC6CC\uD06C \uAC04\uC5D0 \uC27D\uAC8C \uC804\uD658\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uC608\uB97C \uB4E4\uC5B4, PyTorch\uC5D0\uC11C \uD6C8\uB828\uB41C \uBAA8\uB378\uC744 ONNX \uD615\uC2DD\uC73C\uB85C \uB0B4\uBCF4\uB0B4\uACE0 TensorFlow\uC5D0\uC11C \uAC00\uC838\uC62C \uC218 \uC788\uC2B5\uB2C8\uB2E4(\uADF8 \uBC18\uB300\uB3C4 \uAC00\uB2A5\uD569\uB2C8\uB2E4)."),St=m(),Fe=n("p"),ps=o("ONNX \uD615\uC2DD\uC73C\uB85C \uB0B4\uBCF4\uB0B8 \uBAA8\uB378\uC740 \uB2E4\uC74C\uACFC \uAC19\uC774 \uC0AC\uC6A9\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4:"),Ht=m(),x=n("ul"),F=n("li"),ae=n("a"),is=o("\uADF8\uB798\uD504 \uCD5C\uC801\uD654"),ms=o(" \uBC0F "),pe=n("a"),fs=o("\uC591\uC790\uD654"),us=o("\uC640 \uAC19\uC740 \uAE30\uBC95\uC744 \uC0AC\uC6A9\uD558\uC5EC \uCD94\uB860\uC744 \uC704\uD574 \uCD5C\uC801\uD654\uB429\uB2C8\uB2E4."),cs=m(),O=n("li"),ds=o("ONNX Runtime\uC744 \uD1B5\uD574 \uC2E4\uD589\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. "),z=n("a"),pt=n("code"),hs=o("ORTModelForXXX"),bs=o(" \uD074\uB798\uC2A4\uB4E4"),ys=o("\uC744 \uD1B5\uD574 \uB3D9\uC77C\uD55C "),it=n("code"),Ns=o("AutoModel"),ws=o(" API\uB97C \uB530\uB985\uB2C8\uB2E4. \uC774 API\uB294 \u{1F917} Transformers\uC5D0\uC11C \uC0AC\uC6A9\uD558\uB294 \uAC83\uACFC \uB3D9\uC77C\uD569\uB2C8\uB2E4."),Ms=m(),A=n("li"),ie=n("a"),vs=o("\uCD5C\uC801\uD654\uB41C \uCD94\uB860 \uD30C\uC774\uD504\uB77C\uC778"),Ts=o("\uC744 \uC0AC\uC6A9\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uC774\uB294 \u{1F917} Transformers\uC758 "),mt=n("code"),_s=o("pipeline()"),Js=o(" \uD568\uC218\uC640 \uB3D9\uC77C\uD55C API\uB97C \uAC00\uC9C0\uACE0 \uC788\uC2B5\uB2C8\uB2E4."),Qt=m(),ze=n("p"),$s=o("\u{1F917} Optimum\uC740 \uAD6C\uC131 \uAC1D\uCCB4\uB97C \uD65C\uC6A9\uD558\uC5EC ONNX \uB0B4\uBCF4\uB0B4\uAE30\uB97C \uC9C0\uC6D0\uD569\uB2C8\uB2E4. \uC774\uB7EC\uD55C \uAD6C\uC131 \uAC1D\uCCB4\uB294 \uC5EC\uB7EC \uBAA8\uB378 \uC544\uD0A4\uD14D\uCC98\uC5D0 \uB300\uD574 \uBBF8\uB9AC \uC900\uBE44\uB418\uC5B4 \uC788\uC73C\uBA70 \uB2E4\uB978 \uC544\uD0A4\uD14D\uCC98\uC5D0 \uC27D\uAC8C \uD655\uC7A5\uD560 \uC218 \uC788\uB3C4\uB85D \uC124\uACC4\uB418\uC5C8\uC2B5\uB2C8\uB2E4."),Yt=m(),S=n("p"),Xs=o("\uBBF8\uB9AC \uC900\uBE44\uB41C \uAD6C\uC131 \uBAA9\uB85D\uC740 "),me=n("a"),Es=o("\u{1F917} Optimum \uBB38\uC11C"),gs=o("\uB97C \uCC38\uC870\uD558\uC138\uC694."),Pt=m(),Ae=n("p"),xs=o("\u{1F917} Transformers \uBAA8\uB378\uC744 ONNX\uB85C \uB0B4\uBCF4\uB0B4\uB294 \uB450 \uAC00\uC9C0 \uBC29\uBC95\uC774 \uC788\uC2B5\uB2C8\uB2E4. \uC5EC\uAE30\uC5D0\uC11C \uB450 \uAC00\uC9C0 \uBC29\uBC95\uC744 \uBAA8\uB450 \uBCF4\uC5EC\uC90D\uB2C8\uB2E4:"),qt=m(),H=n("ul"),ft=n("li"),Us=o("\u{1F917} Optimum\uC744 \uC0AC\uC6A9\uD558\uC5EC CLI\uB85C \uB0B4\uBCF4\uB0B4\uAE30"),js=m(),Se=n("li"),ut=n("code"),Zs=o("optimum.onnxruntime"),ks=o("\uC744 \uC0AC\uC6A9\uD558\uC5EC \u{1F917} Optimum\uC73C\uB85C ONNX\uB85C \uB0B4\uBCF4\uB0B4\uAE30"),Lt=m(),R=n("h3"),Q=n("a"),ct=n("span"),c(fe.$$.fragment),Os=m(),dt=n("span"),Rs=o("CLI\uB97C \uC0AC\uC6A9\uD558\uC5EC \u{1F917} Transformers \uBAA8\uB378\uC744 ONNX\uB85C \uB0B4\uBCF4\uB0B4\uAE30"),Dt=m(),He=n("p"),Ws=o("\u{1F917} Transformers \uBAA8\uB378\uC744 ONNX\uB85C \uB0B4\uBCF4\uB0B4\uB824\uBA74 \uBA3C\uC800 \uCD94\uAC00 \uC885\uC18D\uC131\uC744 \uC124\uCE58\uD558\uC138\uC694:"),Kt=m(),c(ue.$$.fragment),el=m(),Y=n("p"),Gs=o("\uC0AC\uC6A9 \uAC00\uB2A5\uD55C \uBAA8\uB4E0 \uC778\uC218\uB97C \uD655\uC778\uD558\uB824\uBA74 "),ce=n("a"),Cs=o("\u{1F917} Optimum \uBB38\uC11C"),Bs=o("\uB97C \uCC38\uC870\uD558\uAC70\uB098 \uBA85\uB839\uC904\uC5D0\uC11C \uB3C4\uC6C0\uB9D0\uC744 \uBCF4\uC138\uC694."),tl=m(),c(de.$$.fragment),ll=m(),P=n("p"),Vs=o("\uC608\uB97C \uB4E4\uC5B4, \u{1F917} Hub\uC5D0\uC11C "),ht=n("code"),Is=o("distilbert-base-uncased-distilled-squad"),Fs=o("\uC640 \uAC19\uC740 \uBAA8\uB378\uC758 \uCCB4\uD06C\uD3EC\uC778\uD2B8\uB97C \uB0B4\uBCF4\uB0B4\uB824\uBA74 \uB2E4\uC74C \uBA85\uB839\uC744 \uC2E4\uD589\uD558\uC138\uC694:"),sl=m(),c(he.$$.fragment),ol=m(),q=n("p"),zs=o("\uC704\uC640 \uAC19\uC774 \uC9C4\uD589 \uC0C1\uD669\uC744 \uB098\uD0C0\uB0B4\uB294 \uB85C\uADF8\uAC00 \uD45C\uC2DC\uB418\uACE0 \uACB0\uACFC\uC778 "),bt=n("code"),As=o("model.onnx"),Ss=o("\uAC00 \uC800\uC7A5\uB41C \uC704\uCE58\uAC00 \uD45C\uC2DC\uB429\uB2C8\uB2E4."),rl=m(),c(be.$$.fragment),nl=m(),w=n("p"),Hs=o("\uC704\uC758 \uC608\uC81C\uB294 \u{1F917} Hub\uC5D0\uC11C \uCCB4\uD06C\uD3EC\uC778\uD2B8\uB97C \uB0B4\uBCF4\uB0B4\uB294 \uAC83\uC744 \uC124\uBA85\uD569\uB2C8\uB2E4. \uB85C\uCEEC \uBAA8\uB378\uC744 \uB0B4\uBCF4\uB0BC \uB54C\uC5D0\uB294 \uBAA8\uB378\uC758 \uAC00\uC911\uCE58\uC640 \uD1A0\uD06C\uB098\uC774\uC800 \uD30C\uC77C\uC744 \uB3D9\uC77C\uD55C \uB514\uB809\uD1A0\uB9AC("),yt=n("code"),Qs=o("local_path"),Ys=o(")\uC5D0 \uC800\uC7A5\uD588\uB294\uC9C0 \uD655\uC778\uD558\uC138\uC694. CLI\uB97C \uC0AC\uC6A9\uD560 \uB54C\uC5D0\uB294 \u{1F917} Hub\uC758 \uCCB4\uD06C\uD3EC\uC778\uD2B8 \uC774\uB984 \uB300\uC2E0 "),Nt=n("code"),Ps=o("model"),qs=o(" \uC778\uC218\uC5D0 "),wt=n("code"),Ls=o("local_path"),Ds=o("\uB97C \uC804\uB2EC\uD558\uACE0 "),Mt=n("code"),Ks=o("--task"),eo=o(" \uC778\uC218\uB97C \uC81C\uACF5\uD558\uC138\uC694. \uC9C0\uC6D0\uB418\uB294 \uC791\uC5C5\uC758 \uBAA9\uB85D\uC740 "),ye=n("a"),to=o("\u{1F917} Optimum \uBB38\uC11C"),lo=o("\uB97C \uCC38\uC870\uD558\uC138\uC694. "),vt=n("code"),so=o("task"),oo=o(" \uC778\uC218\uAC00 \uC81C\uACF5\uB418\uC9C0 \uC54A\uC73C\uBA74 \uC791\uC5C5\uC5D0 \uD2B9\uD654\uB41C \uD5E4\uB4DC \uC5C6\uC774 \uBAA8\uB378 \uC544\uD0A4\uD14D\uCC98\uB85C \uAE30\uBCF8 \uC124\uC815\uB429\uB2C8\uB2E4."),al=m(),c(Ne.$$.fragment),pl=m(),X=n("p"),ro=o("\uADF8 \uACB0\uACFC\uB85C \uC0DD\uC131\uB41C "),Tt=n("code"),no=o("model.onnx"),ao=o(" \uD30C\uC77C\uC740 ONNX \uD45C\uC900\uC744 \uC9C0\uC6D0\uD558\uB294 \uB9CE\uC740 "),we=n("a"),po=o("\uAC00\uC18D\uAE30"),io=o(" \uC911 \uD558\uB098\uC5D0\uC11C \uC2E4\uD589\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4. \uC608\uB97C \uB4E4\uC5B4, "),Me=n("a"),mo=o("ONNX Runtime"),fo=o("\uC744 \uC0AC\uC6A9\uD558\uC5EC \uBAA8\uB378\uC744 \uB85C\uB4DC\uD558\uACE0 \uC2E4\uD589\uD560 \uC218 \uC788\uC2B5\uB2C8\uB2E4:"),il=m(),c(ve.$$.fragment),ml=m(),L=n("p"),uo=o("Hub\uC758 TensorFlow \uCCB4\uD06C\uD3EC\uC778\uD2B8\uC5D0 \uB300\uD574\uC11C\uB3C4 \uB3D9\uC77C\uD55C \uD504\uB85C\uC138\uC2A4\uAC00 \uC801\uC6A9\uB429\uB2C8\uB2E4. \uC608\uB97C \uB4E4\uC5B4, "),Te=n("a"),co=o("Keras organization"),ho=o("\uC5D0\uC11C \uC21C\uC218\uD55C TensorFlow \uCCB4\uD06C\uD3EC\uC778\uD2B8\uB97C \uB0B4\uBCF4\uB0B4\uB294 \uBC29\uBC95\uC740 \uB2E4\uC74C\uACFC \uAC19\uC2B5\uB2C8\uB2E4:"),fl=m(),c(_e.$$.fragment),ul=m(),W=n("h3"),D=n("a"),_t=n("span"),c(Je.$$.fragment),bo=m(),Qe=n("span"),Jt=n("code"),yo=o("optimum.onnxruntime"),No=o("\uC744 \uC0AC\uC6A9\uD558\uC5EC \u{1F917} Transformers \uBAA8\uB378\uC744 ONNX\uB85C \uB0B4\uBCF4\uB0B4\uAE30"),cl=m(),K=n("p"),wo=o("CLI \uB300\uC2E0\uC5D0 "),$t=n("code"),Mo=o("optimum.onnxruntime"),vo=o("\uC744 \uC0AC\uC6A9\uD558\uC5EC \uD504\uB85C\uADF8\uB798\uBC0D \uBC29\uC2DD\uC73C\uB85C \u{1F917} Transformers \uBAA8\uB378\uC744 ONNX\uB85C \uB0B4\uBCF4\uB0BC \uC218\uB3C4 \uC788\uC2B5\uB2C8\uB2E4. \uB2E4\uC74C\uACFC \uAC19\uC774 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