diffusers/main/en/_app/pages/api/configuration.mdx-hf-doc-builder.js

import{S as Ft,i as Bt,s as Ht,e as a,k as f,w as k,t,M as Yt,c as s,d as o,m as h,a as i,x as S,h as n,b as c,G as e,g as E,y as T,q as D,o as N,B as j,v as qt,L as zt}from"../../chunks/vendor-hf-doc-builder.js";import{T as Qt}from"../../chunks/Tip-hf-doc-builder.js";import{D as be}from"../../chunks/Docstring-hf-doc-builder.js";import{C as Xt}from"../../chunks/CodeBlock-hf-doc-builder.js";import{I as Vt}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{E as Kt}from"../../chunks/ExampleCodeBlock-hf-doc-builder.js";function en(ie){let l,$,g,m,b,d,y,A;return{c(){l=a("p"),$=t("To use private or "),g=a("a"),m=t("gated"),b=t(" models, log-in with "),d=a("code"),y=t("huggingface-cli login"),A=t("."),this.h()},l(R){l=s(R,"P",{});var w=i(l);$=n(w,"To use private or "),g=s(w,"A",{href:!0,rel:!0});var v=i(g);m=n(v,"gated"),v.forEach(o),b=n(w," models, log-in with "),d=s(w,"CODE",{});var de=i(d);y=n(de,"huggingface-cli login"),de.forEach(o),A=n(w,"."),w.forEach(o),this.h()},h(){c(g,"href","https://huggingface.co/docs/hub/models-gated#gated-models"),c(g,"rel","nofollow")},m(R,w){E(R,l,w),e(l,$),e(l,g),e(g,m),e(l,b),e(l,d),e(d,y),e(l,A)},d(R){R&&o(l)}}}function on(ie){let l,$,g,m,b;return m=new Xt({props:{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DDPMScheduler, DDIMScheduler, PNDMScheduler

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Download scheduler from huggingface.co and cache.</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>scheduler = DDPMScheduler.from_pretrained(<span class="hljs-string">&quot;google/ddpm-cifar10-32&quot;</span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Instantiate DDIM scheduler class with same config as DDPM</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>scheduler = DDIMScheduler.from_config(scheduler.config)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Instantiate PNDM scheduler class with same config as DDPM</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>scheduler = PNDMScheduler.from_config(scheduler.config)`}}),{c(){l=a("p"),$=t("Examples:"),g=f(),k(m.$$.fragment)},l(d){l=s(d,"P",{});var y=i(l);$=n(y,"Examples:"),y.forEach(o),g=h(d),S(m.$$.fragment,d)},m(d,y){E(d,l,y),e(l,$),E(d,g,y),T(m,d,y),b=!0},p:zt,i(d){b||(D(m.$$.fragment,d),b=!0)},o(d){N(m.$$.fragment,d),b=!1},d(d){d&&o(l),d&&o(g),j(m,d)}}}function tn(ie){let l,$,g,m,b,d,y,A,R,w,v,de,le,Xe,Ke,ce,eo,oo,fe,to,no,ye,ro,ao,Oe,G,Ve,L,O,we,X,so,xe,io,Fe,u,K,lo,x,co,$e,fo,ho,he,uo,go,ue,mo,po,ge,_o,vo,bo,Me,yo,wo,C,I,Ee,xo,$o,Ce,Mo,Eo,me,Co,ko,So,V,ke,To,Do,Se,No,jo,Io,F,Te,Jo,Po,De,Uo,Ao,Ro,M,Ne,Lo,Wo,je,Zo,Go,Ie,Oo,Vo,Je,Fo,Bo,Ho,B,ee,Yo,Pe,qo,zo,J,oe,Qo,Ue,Xo,Ko,H,et,Y,te,ot,W,tt,Ae,nt,rt,pe,at,st,it,q,ne,dt,Re,lt,ct,z,re,ft,Le,ht,Be;return d=new Vt({}),G=new Qt({props:{$$slots:{default:[en]},$$scope:{ctx:ie}}}),X=new Vt({}),K=new be({props:{name:"class diffusers.ConfigMixin",anchor:"diffusers.ConfigMixin",parameters:[],source:"https://github.com/huggingface/diffusers/blob/main/src/diffusers/configuration_utils.py#L82"}}),ee=new be({props:{name:"load_config",anchor:"diffusers.ConfigMixin.load_config",parameters:[{name:"pretrained_model_name_or_path",val:": typing.Union[str, os.PathLike]"},{name:"return_unused_kwargs",val:" = False"},{name:"return_commit_hash",val:" = False"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.ConfigMixin.load_config.pretrained_model_name_or_path",description:`<strong>pretrained_model_name_or_path</strong> (<code>str</code> or <code>os.PathLike</code>, <em>optional</em>) &#x2014;
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