diffusers/main/ko/_app/pages/using-diffusers/custom_pipeline_examples.mdx-hf-doc-builder.js

import{S as Ar,i as xr,s as $r,e as s,k as p,t as r,w as u,M as Hr,c as a,d as e,m as c,a as n,h as o,x as M,b as i,N as xn,G as t,g as y,y as h,L as qr,q as m,o as d,B as J,v as Pr}from"../../chunks/vendor-hf-doc-builder.js";import{I as ol}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as pl}from"../../chunks/CodeBlock-hf-doc-builder.js";function Lr($n){let C,Ue,cl,bs,we,Al,fl,Us,yl,ws,Ts,Te,S,xt,gs,js,$t,Zs,vs,ge,q,Ht,U,xl,Gs,_s,$l,Bs,Is,Hl,Ws,Es,ql,ks,Rs,Pl,Vs,Xs,b,w,Ll,Cs,Ss,Kl,Qs,Ns,Ol,lt,Ds,Ys,tt,ul,et,Hn,Fs,st,Ml,zs,As,T,at,xs,$s,P,Hs,hl,qs,Ps,Ls,nt,it,Ks,Os,rt,la,ta,ot,ml,ea,sa,g,pt,aa,na,ct,ia,ra,ft,yt,oa,pa,ut,ca,fa,Mt,dl,ya,ua,j,ht,Ma,ha,Z,ma,qt,da,Ja,Jl,ba,Ua,bl,wa,Ta,Ul,ga,ja,mt,dt,Za,va,Jt,Ga,_a,bt,wl,Ba,Ia,v,Ut,Wa,Ea,L,ka,Pt,Ra,Va,Xa,wt,Tt,Ca,Sa,gt,Qa,Na,jt,Tl,Da,Ya,G,Zt,Fa,za,vt,Aa,xa,Gt,_t,$a,Ha,Bt,qa,Pa,It,gl,La,je,_,Ka,Lt,Oa,ln,Kt,tn,en,Ot,sn,an,Ze,jl,ve,Zl,nn,Ge,Q,K,le,vl,rn,te,on,_e,Wt,pn,Be,Et,cn,Ie,Gl,We,kt,fn,Ee,_l,Rt,qn,yn,ke,N,O,ee,Bl,un,se,Mn,Re,Vt,hn,Ve,Il,Xe,D,ae,mn,dn,Wl,Jn,bn,Ce,Y,ll,ne,El,Un,ie,wn,Se,Xt,Tn,Qe,kl,Ne,tl,gn,re,jn,Zn,De,Ct,Rl,vn,Vl,Gn,_n,Ye,F,el,oe,Xl,Bn,pe,In,Fe,St,Wn,ze,Cl,Ae,Qt,En,xe,z,sl,ce,Sl,kn,fe,Rn,$e,Nt,Vn,He,A,al,ye,Ql,Xn,ue,Cn,qe,Nl,Pe,x,nl,Me,Dl,Sn,he,Qn,Le,Yl,Ke,Dt,Nn,Oe,$,il,me,Fl,Dn,de,Yn,ls,Yt,Fn,ts,zl,es,Ft,zn,ss,zt,At,Pn,as;return jl=new pl({props:{code:"cGlwZSUyMCUzRCUyMERpZmZ1c2lvblBpcGVsaW5lLmZyb21fcHJldHJhaW5lZCglMEElMjAlMjAlMjAlMjAlMjJDb21wVmlzJTJGc3RhYmxlLWRpZmZ1c2lvbi12MS00JTIyJTJDJTIwY3VzdG9tX3BpcGVsaW5lJTNEJTIyZmlsZW5hbWVfaW5fdGhlX2NvbW11bml0eV9mb2xkZXIlMjIlMEEp",highlighted:`pipe = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>, custom_pipeline=<span class="hljs-string">&quot;filename_in_the_community_folder&quot;</span>
)`}}),vl=new ol({}),Gl=new pl({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> CLIPImageProcessor, CLIPModel
<span class="hljs-keyword">import</span> torch


feature_extractor = CLIPImageProcessor.from_pretrained(<span class="hljs-string">&quot;laion/CLIP-ViT-B-32-laion2B-s34B-b79K&quot;</span>)
clip_model = CLIPModel.from_pretrained(<span class="hljs-string">&quot;laion/CLIP-ViT-B-32-laion2B-s34B-b79K&quot;</span>, torch_dtype=torch.float16)


guided_pipeline = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>,
    custom_pipeline=<span class="hljs-string">&quot;clip_guided_stable_diffusion&quot;</span>,
    clip_model=clip_model,
    feature_extractor=feature_extractor,
    torch_dtype=torch.float16,
)
guided_pipeline.enable_attention_slicing()
guided_pipeline = guided_pipeline.to(<span class="hljs-string">&quot;cuda&quot;</span>)

prompt = <span class="hljs-string">&quot;fantasy book cover, full moon, fantasy forest landscape, golden vector elements, fantasy magic, dark light night, intricate, elegant, sharp focus, illustration, highly detailed, digital painting, concept art, matte, art by WLOP and Artgerm and Albert Bierstadt, masterpiece&quot;</span>

generator = torch.Generator(device=<span class="hljs-string">&quot;cuda&quot;</span>).manual_seed(<span class="hljs-number">0</span>)
images = []
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">4</span>):
    image = guided_pipeline(
        prompt,
        num_inference_steps=<span class="hljs-number">50</span>,
        guidance_scale=<span class="hljs-number">7.5</span>,
        clip_guidance_scale=<span class="hljs-number">100</span>,
        num_cutouts=<span class="hljs-number">4</span>,
        use_cutouts=<span class="hljs-literal">False</span>,
        generator=generator,
    ).images[<span class="hljs-number">0</span>]
    images.append(image)

<span class="hljs-comment"># \uC774\uBBF8\uC9C0 \uB85C\uCEEC\uC5D0 \uC800\uC7A5\uD558\uAE30</span>
<span class="hljs-keyword">for</span> i, img <span class="hljs-keyword">in</span> <span class="hljs-built_in">enumerate</span>(images):
    img.save(<span class="hljs-string">f&quot;./clip_guided_sd/image_<span class="hljs-subst">{i}</span>.png&quot;</span>)`}}),Bl=new ol({}),Il=new pl({props:{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERpZmZ1c2lvblBpcGVsaW5lJTBBJTBBcGlwZSUyMCUzRCUyMERpZmZ1c2lvblBpcGVsaW5lLmZyb21fcHJldHJhaW5lZCglMjJnb29nbGUlMkZkZHBtLWNpZmFyMTAtMzIlMjIlMkMlMjBjdXN0b21fcGlwZWxpbmUlM0QlMjJvbmVfc3RlcF91bmV0JTIyKSUwQXBpcGUoKQ==",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;google/ddpm-cifar10-32&quot;</span>, custom_pipeline=<span class="hljs-string">&quot;one_step_unet&quot;</span>)
pipe()`}}),El=new ol({}),kl=new pl({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">import</span> torch

pipe = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>,
    torch_dtype=torch.float16,
    safety_checker=<span class="hljs-literal">None</span>,  <span class="hljs-comment"># Very important for videos...lots of false positives while interpolating</span>
    custom_pipeline=<span class="hljs-string">&quot;interpolate_stable_diffusion&quot;</span>,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipe.enable_attention_slicing()

frame_filepaths = pipe.walk(
    prompts=[<span class="hljs-string">&quot;a dog&quot;</span>, <span class="hljs-string">&quot;a cat&quot;</span>, <span class="hljs-string">&quot;a horse&quot;</span>],
    seeds=[<span class="hljs-number">42</span>, <span class="hljs-number">1337</span>, <span class="hljs-number">1234</span>],
    num_interpolation_steps=<span class="hljs-number">16</span>,
    output_dir=<span class="hljs-string">&quot;./dreams&quot;</span>,
    batch_size=<span class="hljs-number">4</span>,
    height=<span class="hljs-number">512</span>,
    width=<span class="hljs-number">512</span>,
    guidance_scale=<span class="hljs-number">8.5</span>,
    num_inference_steps=<span class="hljs-number">50</span>,
)`}}),Xl=new ol({}),Cl=new pl({props:{code:"JTIzISUyRnVzciUyRmJpbiUyRmVudiUyMHB5dGhvbjMlMEFmcm9tJTIwZGlmZnVzZXJzJTIwaW1wb3J0JTIwRGlmZnVzaW9uUGlwZWxpbmUlMEFpbXBvcnQlMjBQSUwlMEFpbXBvcnQlMjByZXF1ZXN0cyUwQWZyb20lMjBpbyUyMGltcG9ydCUyMEJ5dGVzSU8lMEFpbXBvcnQlMjB0b3JjaCUwQSUwQSUwQWRlZiUyMGRvd25sb2FkX2ltYWdlKHVybCklM0ElMEElMjAlMjAlMjAlMjByZXNwb25zZSUyMCUzRCUyMHJlcXVlc3RzLmdldCh1cmwpJTBBJTIwJTIwJTIwJTIwcmV0dXJuJTIwUElMLkltYWdlLm9wZW4oQnl0ZXNJTyhyZXNwb25zZS5jb250ZW50KSkuY29udmVydCglMjJSR0IlMjIpJTBBJTBBJTBBcGlwZSUyMCUzRCUyMERpZmZ1c2lvblBpcGVsaW5lLmZyb21fcHJldHJhaW5lZCglMEElMjAlMjAlMjAlMjAlMjJDb21wVmlzJTJGc3RhYmxlLWRpZmZ1c2lvbi12MS00JTIyJTJDJTBBJTIwJTIwJTIwJTIwY3VzdG9tX3BpcGVsaW5lJTNEJTIyc3RhYmxlX2RpZmZ1c2lvbl9tZWdhJTIyJTJDJTBBJTIwJTIwJTIwJTIwdG9yY2hfZHR5cGUlM0R0b3JjaC5mbG9hdDE2JTJDJTBBKSUwQXBpcGUudG8oJTIyY3VkYSUyMiklMEFwaXBlLmVuYWJsZV9hdHRlbnRpb25fc2xpY2luZygpJTBBJTBBJTBBJTIzJTIzJTIzJTIwVGV4dC10by1JbWFnZSUwQSUwQWltYWdlcyUyMCUzRCUyMHBpcGUudGV4dDJpbWcoJTIyQW4lMjBhc3Ryb25hdXQlMjByaWRpbmclMjBhJTIwaG9yc2UlMjIpLmltYWdlcyUwQSUwQSUyMyUyMyUyMyUyMEltYWdlLXRvLUltYWdlJTBBJTBBaW5pdF9pbWFnZSUyMCUzRCUyMGRvd25sb2FkX2ltYWdlKCUwQSUyMCUyMCUyMCUyMCUyMmh0dHBzJTNBJTJGJTJGcmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSUyRkNvbXBWaXMlMkZzdGFibGUtZGlmZnVzaW9uJTJGbWFpbiUyRmFzc2V0cyUyRnN0YWJsZS1zYW1wbGVzJTJGaW1nMmltZyUyRnNrZXRjaC1tb3VudGFpbnMtaW5wdXQuanBnJTIyJTBBKSUwQSUwQXByb21wdCUyMCUzRCUyMCUyMkElMjBmYW50YXN5JTIwbGFuZHNjYXBlJTJDJTIwdHJlbmRpbmclMjBvbiUyMGFydHN0YXRpb24lMjIlMEElMEFpbWFnZXMlMjAlM0QlMjBwaXBlLmltZzJpbWcocHJvbXB0JTNEcHJvbXB0JTJDJTIwaW1hZ2UlM0Rpbml0X2ltYWdlJTJDJTIwc3RyZW5ndGglM0QwLjc1JTJDJTIwZ3VpZGFuY2Vfc2NhbGUlM0Q3LjUpLmltYWdlcyUwQSUwQSUyMyUyMyUyMyUyMElucGFpbnRpbmclMEElMEFpbWdfdXJsJTIwJTNEJTIwJTIyaHR0cHMlM0ElMkYlMkZyYXcuZ2l0aHVidXNlcmNvbnRlbnQuY29tJTJGQ29tcFZpcyUyRmxhdGVudC1kaWZmdXNpb24lMkZtYWluJTJGZGF0YSUyRmlucGFpbnRpbmdfZXhhbXBsZXMlMkZvdmVydHVyZS1jcmVhdGlvbnMtNXNJNmZRZ1lJdW8ucG5nJTIyJTBBbWFza191cmwlMjAlM0QlMjAlMjJodHRwcyUzQSUyRiUyRnJhdy5naXRodWJ1c2VyY29udGVudC5jb20lMkZDb21wVmlzJTJGbGF0ZW50LWRpZmZ1c2lvbiUyRm1haW4lMkZkYXRhJTJGaW5wYWludGluZ19leGFtcGxlcyUyRm92ZXJ0dXJlLWNyZWF0aW9ucy01c0k2ZlFnWUl1b19tYXNrLnBuZyUyMiUwQWluaXRfaW1hZ2UlMjAlM0QlMjBkb3dubG9hZF9pbWFnZShpbWdfdXJsKS5yZXNpemUoKDUxMiUyQyUyMDUxMikpJTBBbWFza19pbWFnZSUyMCUzRCUyMGRvd25sb2FkX2ltYWdlKG1hc2tfdXJsKS5yZXNpemUoKDUxMiUyQyUyMDUxMikpJTBBJTBBcHJvbXB0JTIwJTNEJTIwJTIyYSUyMGNhdCUyMHNpdHRpbmclMjBvbiUyMGElMjBiZW5jaCUyMiUwQWltYWdlcyUyMCUzRCUyMHBpcGUuaW5wYWludChwcm9tcHQlM0Rwcm9tcHQlMkMlMjBpbWFnZSUzRGluaXRfaW1hZ2UlMkMlMjBtYXNrX2ltYWdlJTNEbWFza19pbWFnZSUyQyUyMHN0cmVuZ3RoJTNEMC43NSkuaW1hZ2Vz",highlighted:`<span class="hljs-comment">#!/usr/bin/env python3</span>
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">import</span> PIL
<span class="hljs-keyword">import</span> requests
<span class="hljs-keyword">from</span> io <span class="hljs-keyword">import</span> BytesIO
<span class="hljs-keyword">import</span> torch


<span class="hljs-keyword">def</span> <span class="hljs-title function_">download_image</span>(<span class="hljs-params">url</span>):
    response = requests.get(url)
    <span class="hljs-keyword">return</span> PIL.Image.<span class="hljs-built_in">open</span>(BytesIO(response.content)).convert(<span class="hljs-string">&quot;RGB&quot;</span>)


pipe = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>,
    custom_pipeline=<span class="hljs-string">&quot;stable_diffusion_mega&quot;</span>,
    torch_dtype=torch.float16,
)
pipe.to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipe.enable_attention_slicing()


<span class="hljs-comment">### Text-to-Image</span>

images = pipe.text2img(<span class="hljs-string">&quot;An astronaut riding a horse&quot;</span>).images

<span class="hljs-comment">### Image-to-Image</span>

init_image = download_image(
    <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg&quot;</span>
)

prompt = <span class="hljs-string">&quot;A fantasy landscape, trending on artstation&quot;</span>

images = pipe.img2img(prompt=prompt, image=init_image, strength=<span class="hljs-number">0.75</span>, guidance_scale=<span class="hljs-number">7.5</span>).images

<span class="hljs-comment">### Inpainting</span>

img_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png&quot;</span>
mask_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png&quot;</span>
init_image = download_image(img_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>))
mask_image = download_image(mask_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>))

prompt = <span class="hljs-string">&quot;a cat sitting on a bench&quot;</span>
images = pipe.inpaint(prompt=prompt, image=init_image, mask_image=mask_image, strength=<span class="hljs-number">0.75</span>).images`}}),Sl=new ol({}),Ql=new ol({}),Nl=new pl({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">import</span> torch

pipe = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;hakurei/waifu-diffusion&quot;</span>, custom_pipeline=<span class="hljs-string">&quot;lpw_stable_diffusion&quot;</span>, torch_dtype=torch.float16
)
pipe = pipe.to(<span class="hljs-string">&quot;cuda&quot;</span>)

prompt = <span class="hljs-string">&quot;best_quality (1girl:1.3) bow bride brown_hair closed_mouth frilled_bow frilled_hair_tubes frills (full_body:1.3) fox_ear hair_bow hair_tubes happy hood japanese_clothes kimono long_sleeves red_bow smile solo tabi uchikake white_kimono wide_sleeves cherry_blossoms&quot;</span>
neg_prompt = <span class="hljs-string">&quot;lowres, bad_anatomy, error_body, error_hair, error_arm, error_hands, bad_hands, error_fingers, bad_fingers, missing_fingers, error_legs, bad_legs, multiple_legs, missing_legs, error_lighting, error_shadow, error_reflection, text, error, extra_digit, fewer_digits, cropped, worst_quality, low_quality, normal_quality, jpeg_artifacts, signature, watermark, username, blurry&quot;</span>

pipe.text2img(prompt, negative_prompt=neg_prompt, width=<span class="hljs-number">512</span>, height=<span class="hljs-number">512</span>, max_embeddings_multiples=<span class="hljs-number">3</span>).images[<span class="hljs-number">0</span>]`}}),Dl=new ol({}),Yl=new pl({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">import</span> torch

pipe = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>,
    custom_pipeline=<span class="hljs-string">&quot;lpw_stable_diffusion_onnx&quot;</span>,
    revision=<span class="hljs-string">&quot;onnx&quot;</span>,
    provider=<span class="hljs-string">&quot;CUDAExecutionProvider&quot;</span>,
)

prompt = <span class="hljs-string">&quot;a photo of an astronaut riding a horse on mars, best quality&quot;</span>
neg_prompt = <span class="hljs-string">&quot;lowres, bad anatomy, error body, error hair, error arm, error hands, bad hands, error fingers, bad fingers, missing fingers, error legs, bad legs, multiple legs, missing legs, error lighting, error shadow, error reflection, text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry&quot;</span>

pipe.text2img(prompt, negative_prompt=neg_prompt, width=<span class="hljs-number">512</span>, height=<span class="hljs-number">512</span>, max_embeddings_multiples=<span class="hljs-number">3</span>).images[<span class="hljs-number">0</span>]`}}),Fl=new ol({}),zl=new pl({props:{code:"aW1wb3J0JTIwdG9yY2glMEElMEFpbXBvcnQlMjBtYXRwbG90bGliLnB5cGxvdCUyMGFzJTIwcGx0JTBBZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERpZmZ1c2lvblBpcGVsaW5lJTBBZnJvbSUyMHRyYW5zZm9ybWVycyUyMGltcG9ydCUyMCglMEElMjAlMjAlMjAlMjBXaGlzcGVyRm9yQ29uZGl0aW9uYWxHZW5lcmF0aW9uJTJDJTBBJTIwJTIwJTIwJTIwV2hpc3BlclByb2Nlc3NvciUyQyUwQSklMEElMEElMEFkZXZpY2UlMjAlM0QlMjAlMjJjdWRhJTIyJTIwaWYlMjB0b3JjaC5jdWRhLmlzX2F2YWlsYWJsZSgpJTIwZWxzZSUyMCUyMmNwdSUyMiUwQSUwQWRzJTIwJTNEJTIwbG9hZF9kYXRhc2V0KCUyMmhmLWludGVybmFsLXRlc3RpbmclMkZsaWJyaXNwZWVjaF9hc3JfZHVtbXklMjIlMkMlMjAlMjJjbGVhbiUyMiUyQyUyMHNwbGl0JTNEJTIydmFsaWRhdGlvbiUyMiklMEElMEFhdWRpb19zYW1wbGUlMjAlM0QlMjBkcyU1QjMlNUQlMEElMEF0ZXh0JTIwJTNEJTIwYXVkaW9fc2FtcGxlJTVCJTIydGV4dCUyMiU1RC5sb3dlcigpJTBBc3BlZWNoX2RhdGElMjAlM0QlMjBhdWRpb19zYW1wbGUlNUIlMjJhdWRpbyUyMiU1RCU1QiUyMmFycmF5JTIyJTVEJTBBJTBBbW9kZWwlMjAlM0QlMjBXaGlzcGVyRm9yQ29uZGl0aW9uYWxHZW5lcmF0aW9uLmZyb21fcHJldHJhaW5lZCglMjJvcGVuYWklMkZ3aGlzcGVyLXNtYWxsJTIyKS50byhkZXZpY2UpJTBBcHJvY2Vzc29yJTIwJTNEJTIwV2hpc3BlclByb2Nlc3Nvci5mcm9tX3ByZXRyYWluZWQoJTIyb3BlbmFpJTJGd2hpc3Blci1zbWFsbCUyMiklMEElMEFkaWZmdXNlcl9waXBlbGluZSUyMCUzRCUyMERpZmZ1c2lvblBpcGVsaW5lLmZyb21fcHJldHJhaW5lZCglMEElMjAlMjAlMjAlMjAlMjJDb21wVmlzJTJGc3RhYmxlLWRpZmZ1c2lvbi12MS00JTIyJTJDJTBBJTIwJTIwJTIwJTIwY3VzdG9tX3BpcGVsaW5lJTNEJTIyc3BlZWNoX3RvX2ltYWdlX2RpZmZ1c2lvbiUyMiUyQyUwQSUyMCUyMCUyMCUyMHNwZWVjaF9tb2RlbCUzRG1vZGVsJTJDJTBBJTIwJTIwJTIwJTIwc3BlZWNoX3Byb2Nlc3NvciUzRHByb2Nlc3NvciUyQyUwQSUyMCUyMCUyMCUyMCUwQSUyMCUyMCUyMCUyMHRvcmNoX2R0eXBlJTNEdG9yY2guZmxvYXQxNiUyQyUwQSklMEElMEFkaWZmdXNlcl9waXBlbGluZS5lbmFibGVfYXR0ZW50aW9uX3NsaWNpbmcoKSUwQWRpZmZ1c2VyX3BpcGVsaW5lJTIwJTNEJTIwZGlmZnVzZXJfcGlwZWxpbmUudG8oZGV2aWNlKSUwQSUwQW91dHB1dCUyMCUzRCUyMGRpZmZ1c2VyX3BpcGVsaW5lKHNwZWVjaF9kYXRhKSUwQXBsdC5pbXNob3cob3V0cHV0LmltYWdlcyU1QjAlNUQp",highlighted:`<span class="hljs-keyword">import</span> torch

<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
<span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> (
    WhisperForConditionalGeneration,
    WhisperProcessor,
)


device = <span class="hljs-string">&quot;cuda&quot;</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">&quot;cpu&quot;</span>

ds = load_dataset(<span class="hljs-string">&quot;hf-internal-testing/librispeech_asr_dummy&quot;</span>, <span class="hljs-string">&quot;clean&quot;</span>, split=<span class="hljs-string">&quot;validation&quot;</span>)

audio_sample = ds[<span class="hljs-number">3</span>]

text = audio_sample[<span class="hljs-string">&quot;text&quot;</span>].lower()
speech_data = audio_sample[<span class="hljs-string">&quot;audio&quot;</span>][<span class="hljs-string">&quot;array&quot;</span>]

model = WhisperForConditionalGeneration.from_pretrained(<span class="hljs-string">&quot;openai/whisper-small&quot;</span>).to(device)
processor = WhisperProcessor.from_pretrained(<span class="hljs-string">&quot;openai/whisper-small&quot;</span>)

diffuser_pipeline = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>,
    custom_pipeline=<span class="hljs-string">&quot;speech_to_image_diffusion&quot;</span>,
    speech_model=model,
    speech_processor=processor,
    
    torch_dtype=torch.float16,
)

diffuser_pipeline.enable_attention_slicing()
diffuser_pipeline = diffuser_pipeline.to(device)

output = diffuser_pipeline(speech_data)
plt.imshow(output.images[<span class="hljs-number">0</span>])`}}),{c(){C=s("meta"),Ue=p(),cl=s("h1"),bs=r("\uCEE4\uBBA4\uB2C8\uD2F0 \uD30C\uC774\uD504\uB77C\uC778"),we=p(),Al=s("blockquote"),fl=s("p"),Us=r("**\uCEE4\uBBA4\uB2C8\uD2F0 \uD30C\uC774\uD504\uB77C\uC778\uC5D0 \uB300\uD55C \uC790\uC138\uD55C \uB0B4\uC6A9\uC740 "),yl=s("a"),ws=r("\uC774 \uC774\uC288"),Ts=r("\uB97C \uCC38\uC870\uD558\uC138\uC694."),Te=p(),S=s("p"),xt=s("strong"),gs=r("\uCEE4\uBBA4\uB2C8\uD2F0"),js=r(` \uC608\uC81C\uB294 \uCEE4\uBBA4\uB2C8\uD2F0\uC5D0\uC11C \uCD94\uAC00\uD55C \uCD94\uB860 \uBC0F \uD6C8\uB828 \uC608\uC81C\uB85C \uAD6C\uC131\uB418\uC5B4 \uC788\uC2B5\uB2C8\uB2E4.
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