import{S as Er,i as yr,s as $r,e as o,k as h,w as d,t as n,M as Tr,c as a,d as t,m as u,a as r,x as c,h as f,b as s,N as Sr,G as l,g as p,y as m,L as xr,q as v,o as b,B as w,v as Nr}from"../../chunks/vendor-hf-doc-builder.js";import{I as E}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as Ge}from"../../chunks/CodeBlock-hf-doc-builder.js";function gr(ta){let y,Rt,$,G,Ie,z,Il,Oe,Ol,Gt,I,jl,K,Wl,Xl,It,T,O,je,ee,Dl,We,Zl,Ot,ke,Pl,jt,te,Wt,S,j,Xe,le,Bl,De,Cl,Xt,x,W,Ze,oe,Al,Pe,Hl,Dt,_,Ll,Me,Vl,Fl,Be,Yl,Ql,Ce,ql,zl,Zt,ae,Pt,X,Kl,re,Ae,eo,to,Bt,ie,Ct,Je,lo,At,se,Ht,D,oo,He,ao,ro,Lt,ne,Le,la,Vt,Z,io,fe,so,no,Ft,N,P,Ve,pe,fo,Fe,po,Yt,B,Ye,he,Qe,ho,uo,qe,co,mo,g,ue,ze,Ke,vo,bo,et,tt,wo,_o,de,lt,ot,Eo,yo,at,rt,$o,To,ce,it,st,So,xo,nt,ft,No,Qt,k,C,pt,me,go,ht,ko,qt,M,A,ut,ve,Mo,dt,Jo,zt,H,Uo,be,Ro,Go,Kt,we,el,J,L,ct,_e,Io,mt,Oo,tl,V,jo,Ee,Wo,Xo,ll,ye,ol,U,F,vt,$e,Do,bt,Zo,al,Y,wt,Te,_t,Po,Bo,Et,Co,Ao,Se,xe,yt,$t,Ho,Lo,Tt,St,Vo,Fo,Ne,xt,Nt,Yo,Qo,gt,kt,qo,rl,R,Q,Mt,ge,zo,Jt,Ko,il,Ue,Ut,ea,sl;return z=new E({}),ee=new E({}),te=new Ge({props:{code:"cGlwJTIwaW5zdGFsbCUyMG9wdGltdW0lNUIlMjJvbm54cnVudGltZSUyMiU1RA==",highlighted:'pip <span class="hljs-keyword">install</span> optimum[<span class="hljs-string">&quot;onnxruntime&quot;</span>]'}}),le=new E({}),oe=new E({}),ae=new Ge({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.onnxruntime <span class="hljs-keyword">import</span> ORTStableDiffusionPipeline

model_id = <span class="hljs-string">&quot;runwayml/stable-diffusion-v1-5&quot;</span>
pipeline = ORTStableDiffusionPipeline.from_pretrained(model_id, export=<span class="hljs-literal">True</span>)
prompt = <span class="hljs-string">&quot;sailing ship in storm by Leonardo da Vinci&quot;</span>
image = pipeline(prompt).images[<span class="hljs-number">0</span>]
pipeline.save_pretrained(<span class="hljs-string">&quot;./onnx-stable-diffusion-v1-5&quot;</span>)`}}),ie=new Ge({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1tb2RlbCUyMHJ1bndheW1sJTJGc3RhYmxlLWRpZmZ1c2lvbi12MS01JTIwc2RfdjE1X29ubnglMkY=",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --model runwayml/stable-diffusion-v1-5 sd_v15_onnx/'}}),se=new Ge({props:{code:"ZnJvbSUyMG9wdGltdW0ub25ueHJ1bnRpbWUlMjBpbXBvcnQlMjBPUlRTdGFibGVEaWZmdXNpb25QaXBlbGluZSUwQSUwQW1vZGVsX2lkJTIwJTNEJTIwJTIyc2RfdjE1X29ubnglMjIlMEFwaXBlbGluZSUyMCUzRCUyME9SVFN0YWJsZURpZmZ1c2lvblBpcGVsaW5lLmZyb21fcHJldHJhaW5lZChtb2RlbF9pZCklMEFwcm9tcHQlMjAlM0QlMjAlMjJzYWlsaW5nJTIwc2hpcCUyMGluJTIwc3Rvcm0lMjBieSUyMExlb25hcmRvJTIwZGElMjBWaW5jaSUyMiUwQWltYWdlJTIwJTNEJTIwcGlwZWxpbmUocHJvbXB0KS5pbWFnZXMlNUIwJTVE",highlighted:`<span class="hljs-keyword">from</span> optimum.onnxruntime <span class="hljs-keyword">import</span> ORTStableDiffusionPipeline

model_id = <span class="hljs-string">&quot;sd_v15_onnx&quot;</span>
pipeline = ORTStableDiffusionPipeline.from_pretrained(model_id)
prompt = <span class="hljs-string">&quot;sailing ship in storm by Leonardo da Vinci&quot;</span>
image = pipeline(prompt).images[<span class="hljs-number">0</span>]`}}),pe=new E({}),me=new E({}),ve=new E({}),we=new Ge({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1tb2RlbCUyMHN0YWJpbGl0eWFpJTJGc3RhYmxlLWRpZmZ1c2lvbi14bC1iYXNlLTEuMCUyMC0tdGFzayUyMHN0YWJsZS1kaWZmdXNpb24teGwlMjBzZF94bF9vbm54JTJG",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --model stabilityai/stable-diffusion-xl-base-1.0 --task stable-diffusion-xl sd_xl_onnx/'}}),_e=new E({}),ye=new Ge({props:{code:"ZnJvbSUyMG9wdGltdW0ub25ueHJ1bnRpbWUlMjBpbXBvcnQlMjBPUlRTdGFibGVEaWZmdXNpb25YTFBpcGVsaW5lJTBBJTBBbW9kZWxfaWQlMjAlM0QlMjAlMjJzdGFiaWxpdHlhaSUyRnN0YWJsZS1kaWZmdXNpb24teGwtYmFzZS0xLjAlMjIlMEFwaXBlbGluZSUyMCUzRCUyME9SVFN0YWJsZURpZmZ1c2lvblhMUGlwZWxpbmUuZnJvbV9wcmV0cmFpbmVkKG1vZGVsX2lkKSUwQXByb21wdCUyMCUzRCUyMCUyMnNhaWxpbmclMjBzaGlwJTIwaW4lMjBzdG9ybSUyMGJ5JTIwTGVvbmFyZG8lMjBkYSUyMFZpbmNpJTIyJTBBaW1hZ2UlMjAlM0QlMjBwaXBlbGluZShwcm9tcHQpLmltYWdlcyU1QjAlNUQ=",highlighted:`<span class="hljs-keyword">from</span> optimum.onnxruntime <span class="hljs-keyword">import</span> ORTStableDiffusionXLPipeline

model_id = <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>
pipeline = ORTStableDiffusionXLPipeline.from_pretrained(model_id)
prompt = <span class="hljs-string">&quot;sailing ship in storm by Leonardo da Vinci&quot;</span>
image = pipeline(prompt).images[<span class="hljs-number">0</span>]`}}),$e=new E({}),ge=new E({}),{c(){y=o("meta"),Rt=h(),$=o("h1"),G=o("a"),Ie=o("span"),d(z.$$.fragment),Il=h(),Oe=o("span"),Ol=n("How to use ONNX Runtime for inference"),Gt=h(),I=o("p"),jl=n("\u{1F917} "),K=o("a"),Wl=n("Optimum"),Xl=n(" provides a Stable Diffusion pipeline compatible with ONNX Runtime."),It=h(),T=o("h2"),O=o("a"),je=o("span"),d(ee.$$.fragment),Dl=h(),We=o("span"),Zl=n("Installation"),Ot=h(),ke=o("p"),Pl=n("Install \u{1F917} Optimum with the following command for ONNX Runtime support:"),jt=h(),d(te.$$.fragment),Wt=h(),S=o("h2"),j=o("a"),Xe=o("span"),d(le.$$.fragment),Bl=h(),De=o("span"),Cl=n("Stable Diffusion"),Xt=h(),x=o("h3"),W=o("a"),Ze=o("span"),d(oe.$$.fragment),Al=h(),Pe=o("span"),Hl=n("Inference"),Dt=h(),_=o("p"),Ll=n("To load an ONNX model and run inference with ONNX Runtime, you need to replace "),Me=o("a"),Vl=n("StableDiffusionPipeline"),Fl=n(" with "),Be=o("code"),Yl=n("ORTStableDiffusionPipeline"),Ql=n(". In case you want to load a PyTorch model and convert it to the ONNX format on-the-fly, you can set "),Ce=o("code"),ql=n("export=True"),zl=n("."),Zt=h(),d(ae.$$.fragment),Pt=h(),X=o("p"),Kl=n(`If you want to export the pipeline in the ONNX format offline and later use it for inference,
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