import{S as Nf,i as Cf,s as jf,e as a,k as f,w as ne,t as i,M as Vf,c as l,d as t,m as d,a as r,x as fe,h as s,b as n,N as Hl,G as e,g as h,y as de,L as Jf,q as ce,o as he,B as ue,v as Lf}from"../../../../chunks/vendor-hf-doc-builder.js";import{D as Wf}from"../../../../chunks/Docstring-hf-doc-builder.js";import{C as $f}from"../../../../chunks/CodeBlock-hf-doc-builder.js";import{I as il}from"../../../../chunks/IconCopyLink-hf-doc-builder.js";function Bf(gs){let k,sl,R,J,Ht,pe,Ql,Qt,zl,nl,v,Fl,zt,Yl,ql,me,Kl,er,ge,tr,ar,ve,lr,rr,Ee,or,ir,fl,A,sr,be,nr,fr,at,dr,cr,dl,U,hr,_e,ur,pr,De,mr,gr,cl,we,Ft,vr,Er,hl,lt,rt,br,ye,ot,vs,ul,Te,Yt,_r,Dr,pl,L,qt,b,Kt,wr,yr,ea,Tr,Sr,it,xr,Ir,st,Mr,Pr,u,_,ta,nt,Gr,Zr,aa,la,Ar,Ur,ft,Se,dt,Es,kr,ct,xe,Rr,$r,D,ra,ht,Nr,Cr,oa,ia,jr,Vr,ut,Ie,pt,bs,Jr,mt,Me,Lr,Wr,w,sa,gt,Br,Or,Pe,na,Xr,Hr,fa,Qr,zr,vt,Ge,Et,_s,Fr,bt,Yr,qr,y,da,_t,Kr,eo,Ze,ca,to,ao,ha,lo,ro,ua,oo,Dt,io,so,T,pa,wt,no,fo,Ae,ma,co,ho,ga,uo,po,va,mo,yt,Ue,go,vo,S,Ea,Tt,Eo,bo,ke,ba,_o,Do,_a,wo,yo,Da,To,St,So,xo,x,wa,xt,Io,Mo,Re,ya,Po,Go,Ta,Zo,Ao,Sa,Uo,It,ko,Ro,I,xa,Mt,$o,No,$e,Ia,Co,jo,Ma,Vo,Jo,Pa,Lo,Pt,Ne,Wo,Bo,M,Ga,Gt,Oo,Xo,Ce,Za,Ho,Qo,Aa,zo,Fo,Ua,Yo,Zt,je,qo,Ko,P,ka,At,ei,ti,Ve,Ra,ai,li,$a,ri,oi,Na,ii,Ut,Je,si,ni,G,Ca,kt,fi,di,Le,ja,ci,hi,Va,ui,pi,Ja,mi,Rt,We,gi,vi,Z,La,$t,Ei,bi,Be,Wa,_i,Di,Ba,wi,yi,Oa,Ti,Nt,Oe,Si,ml,$,W,Xa,Xe,xi,Ha,Ii,gl,N,B,Qa,He,Mi,za,Pi,vl,p,Gi,Ct,Zi,Ai,Fa,Ui,ki,jt,Ri,$i,Vt,Ni,Ci,Jt,ji,Vi,Lt,Ji,Li,Wt,Wi,Bi,Ya,Oi,Xi,qa,Hi,Qi,Bt,zi,Fi,El,Qe,bl,C,O,Ka,ze,Yi,el,qi,_l,X,Ki,tl,es,ts,Dl,H,Fe,as,Ye,ls,rs,os,qe,is,al,ss,ns,wl,Ke,yl,j,Q,ll,et,fs,rl,ds,Tl,V,tt,cs,ol,hs,Sl;return pe=new il({}),Xe=new il({}),He=new il({}),Qe=new $f({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> StableDiffusionPipeline, EulerDiscreteScheduler

<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline = StableDiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.scheduler = EulerDiscreteScheduler.from_config(pipeline.scheduler.config)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># or</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>euler_scheduler = EulerDiscreteScheduler.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>, subfolder=<span class="hljs-string">&quot;scheduler&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline = StableDiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>, scheduler=euler_scheduler)`}}),ze=new il({}),Ke=new $f({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> (
<span class="hljs-meta">... </span>    StableDiffusionPipeline,
<span class="hljs-meta">... </span>    StableDiffusionImg2ImgPipeline,
<span class="hljs-meta">... </span>    StableDiffusionInpaintPipeline,
<span class="hljs-meta">... </span>)

<span class="hljs-meta">&gt;&gt;&gt; </span>text2img = StableDiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>img2img = StableDiffusionImg2ImgPipeline(**text2img.components)
<span class="hljs-meta">&gt;&gt;&gt; </span>inpaint = StableDiffusionInpaintPipeline(**text2img.components)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># now you can use text2img(...), img2img(...), inpaint(...) just like the call methods of each respective pipeline</span>`}}),et=new il({}),tt=new Wf({props:{name:"class diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput",anchor:"diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput",parameters:[{name:"images",val:": typing.Union[typing.List[PIL.Image.Image], numpy.ndarray]"},{name:"nsfw_content_detected",val:": typing.Optional[typing.List[bool]]"}],parametersDescription:[{anchor:"diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput.images",description:`<strong>images</strong> (<code>List[PIL.Image.Image]</code> or <code>np.ndarray</code>) &#x2014;
List of denoised PIL images of length <code>batch_size</code> or numpy array of shape <code>(batch_size, height, width, num_channels)</code>. PIL images or numpy array present the denoised images of the diffusion pipeline.`,name:"images"},{anchor:"diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput.nsfw_content_detected",description:`<strong>nsfw_content_detected</strong> (<code>List[bool]</code>) &#x2014;
List of flags denoting whether the corresponding generated image likely represents &#x201C;not-safe-for-work&#x201D;
(nsfw) content, or <code>None</code> if safety checking could not be performed.`,name:"nsfw_content_detected"}],source:"https://github.com/huggingface/diffusers/blob/v0.17.0/src/diffusers/pipelines/stable_diffusion/__init__.py#L22"}}),{c(){k=a("meta"),sl=f(),R=a("h1"),J=a("a"),Ht=a("span"),ne(pe.$$.fragment),Ql=f(),Qt=a("span"),zl=i("Stable diffusion pipelines"),nl=f(),v=a("p"),Fl=i("Stable Diffusion is a text-to-image "),zt=a("em"),Yl=i("latent diffusion"),ql=i(" model created by the researchers and engineers from "),me=a("a"),Kl=i("CompVis"),er=i(", "),ge=a("a"),tr=i("Stability AI"),ar=i(" and "),ve=a("a"),lr=i("LAION"),rr=i(". It\u2019s trained on 512x512 images from a subset of the "),Ee=a("a"),or=i("LAION-5B"),ir=i(" dataset. This model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. 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