diffusers/pr_13881/ko/_app/immutable/nodes/14.B1despPO.js

import"../chunks/DsnmJJEf.js";import{i as U,h as w,C as J,H as l,a as o,E as T,s as v}from"../chunks/CFM6C53a.js";import{p as Z,o as G,s as a,f as B,a as h,b as j,c as f,n as R}from"../chunks/CNc7KuUZ.js";const S='{"title":"추론을 위해 ONNX 런타임을 사용하는 방법","local":"추론을-위해-onnx-런타임을-사용하는-방법","sections":[{"title":"설치","local":"설치","sections":[],"depth":2},{"title":"Stable Diffusion 추론","local":"stable-diffusion-추론","sections":[],"depth":2},{"title":"알려진 이슈들","local":"알려진-이슈들","sections":[],"depth":2}],"depth":1}';var x=f('<meta name="hf:doc:metadata"/>'),N=f(`<p></p> <!> <!> <p>🤗 Diffusers는 ONNX Runtime과 호환되는 Stable Diffusion 파이프라인을 제공합니다. 이를 통해 ONNX(CPU 포함)를 지원하고 PyTorch의 가속 버전을 사용할 수 없는 모든 하드웨어에서 Stable Diffusion을 실행할 수 있습니다.</p> <!> <p>다음 명령어로 ONNX Runtime를 지원하는 🤗 Optimum를 설치합니다:</p> <!> <!> <p>아래 코드는 ONNX 런타임을 사용하는 방법을 보여줍니다. <code>StableDiffusionPipeline</code> 대신 <code>OnnxStableDiffusionPipeline</code>을 사용해야 합니다.
PyTorch 모델을 불러오고 즉시 ONNX 형식으로 변환하려는 경우 <code>export=True</code>로 설정합니다.</p> <!> <p>파이프라인을 ONNX 형식으로 오프라인으로 내보내고 나중에 추론에 사용하려는 경우, <a href="https://huggingface.co/docs/optimum/main/en/exporters/onnx/usage_guides/export_a_model#exporting-a-model-to-onnx-using-the-cli" rel="nofollow"><code>optimum-cli export</code></a> 명령어를 사용할 수 있습니다:</p> <!> <p>그 다음 추론을 수행합니다:</p> <!> <p>Notice that we didn’t have to specify <code>export=True</code> above.</p> <p><a href="https://huggingface.co/docs/optimum/" rel="nofollow">Optimum 문서</a>에서 더 많은 예시를 찾을 수 있습니다.</p> <!> <ul><li>여러 프롬프트를 배치로 생성하면 너무 많은 메모리가 사용되는 것 같습니다. 이를 조사하는 동안, 배치 대신 반복 방법이 필요할 수도 있습니다.</li></ul> <!> <p></p>`,1);function I(y,g){Z(g,!1),G(()=>{new URLSearchParams(window.location.search).get("fw")}),U();var n=N();w("1txzw1m",u=>{var b=x();v(b,"content",S),h(u,b)});var e=a(B(n),2);J(e,{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"});var s=a(e,2);l(s,{title:"추론을 위해 ONNX 런타임을 사용하는 방법",local:"추론을-위해-onnx-런타임을-사용하는-방법",headingTag:"h1"});var i=a(s,4);l(i,{title:"설치",local:"설치",headingTag:"h2"});var t=a(i,4);o(t,{code:"cGlwJTIwaW5zdGFsbCUyMG9wdGltdW0lNUIlMjJvbm54cnVudGltZSUyMiU1RA==",highlighted:'pip install optimum[<span class="hljs-string">&quot;onnxruntime&quot;</span>]',lang:"sh",wrap:!1});var p=a(t,2);l(p,{title:"Stable Diffusion 추론",local:"stable-diffusion-추론",headingTag:"h2"});var d=a(p,4);o(d,{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;stable-diffusion-v1-5/stable-diffusion-v1-5&quot;</span>
pipe = ORTStableDiffusionPipeline.from_pretrained(model_id, export=<span class="hljs-literal">True</span>)
prompt = <span class="hljs-string">&quot;a photo of an astronaut riding a horse on mars&quot;</span>
images = pipe(prompt).images[<span class="hljs-number">0</span>]
pipe.save_pretrained(<span class="hljs-string">&quot;./onnx-stable-diffusion-v1-5&quot;</span>)`,lang:"python",wrap:!1});var r=a(d,4);o(r,{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBvbm54JTIwLS1tb2RlbCUyMHN0YWJsZS1kaWZmdXNpb24tdjEtNSUyRnN0YWJsZS1kaWZmdXNpb24tdjEtNSUyMHNkX3YxNV9vbm54JTJG",highlighted:'optimum-cli <span class="hljs-built_in">export</span> onnx --model stable-diffusion-v1-5/stable-diffusion-v1-5 sd_v15_onnx/',lang:"bash",wrap:!1});var c=a(r,4);o(c,{code:"ZnJvbSUyMG9wdGltdW0ub25ueHJ1bnRpbWUlMjBpbXBvcnQlMjBPUlRTdGFibGVEaWZmdXNpb25QaXBlbGluZSUwQSUwQW1vZGVsX2lkJTIwJTNEJTIwJTIyc2RfdjE1X29ubnglMjIlMEFwaXBlJTIwJTNEJTIwT1JUU3RhYmxlRGlmZnVzaW9uUGlwZWxpbmUuZnJvbV9wcmV0cmFpbmVkKG1vZGVsX2lkKSUwQXByb21wdCUyMCUzRCUyMCUyMmElMjBwaG90byUyMG9mJTIwYW4lMjBhc3Ryb25hdXQlMjByaWRpbmclMjBhJTIwaG9yc2UlMjBvbiUyMG1hcnMlMjIlMEFpbWFnZXMlMjAlM0QlMjBwaXBlKHByb21wdCkuaW1hZ2VzJTVCMCU1RA==",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>
pipe = ORTStableDiffusionPipeline.from_pretrained(model_id)
prompt = <span class="hljs-string">&quot;a photo of an astronaut riding a horse on mars&quot;</span>
images = pipe(prompt).images[<span class="hljs-number">0</span>]`,lang:"python",wrap:!1});var m=a(c,6);l(m,{title:"알려진 이슈들",local:"알려진-이슈들",headingTag:"h2"});var M=a(m,4);T(M,{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/ko/optimization/onnx.md"}),R(2),h(y,n),j()}export{I as component};