diffusers/pr_12762/en/_app/immutable/nodes/185.f6a5fa65.js

import{s as Q,n as F,o as J}from"../chunks/scheduler.53228c21.js";import{S as V,i as Y,e as r,s,c as A,h as Z,a as f,d as i,b as n,f as K,g as H,j as L,k as j,l as ee,m as a,n as z,t as E,o as q,p as O}from"../chunks/index.100fac89.js";import{C as te}from"../chunks/CopyLLMTxtMenu.969c168d.js";import{H as N,E as ie}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.92f39b94.js";function ae(I){let l,x,$,T,u,w,m,v,p,R='Stable Diffusion XL (SDXL) Turbo was proposed in <a href="https://stability.ai/research/adversarial-diffusion-distillation" rel="nofollow">Adversarial Diffusion Distillation</a> by Axel Sauer, Dominik Lorenz, Andreas Blattmann, and Robin Rombach.',y,h,U="The abstract from the paper is:",D,c,B="<em>We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that efficiently samples large-scale foundational image diffusion models in just 1–4 steps while maintaining high image quality. We use score distillation to leverage large-scale off-the-shelf image diffusion models as a teacher signal in combination with an adversarial loss to ensure high image fidelity even in the low-step regime of one or two sampling steps. Our analyses show that our model clearly outperforms existing few-step methods (GANs,Latent Consistency Models) in a single step and reaches the performance of state-of-the-art diffusion models (SDXL) in only four steps. ADD is the first method to unlock single-step, real-time image synthesis with foundation models.</em>",S,d,M,g,G='<li>SDXL Turbo uses the exact same architecture as <a href="./stable_diffusion_xl">SDXL</a>, which means it also has the same API. Please refer to the <a href="./stable_diffusion_xl">SDXL</a> API reference for more details.</li> <li>SDXL Turbo should disable guidance scale by setting <code>guidance_scale=0.0</code>.</li> <li>SDXL Turbo should use <code>timestep_spacing=&#39;trailing&#39;</code> for the scheduler and use between 1 and 4 steps.</li> <li>SDXL Turbo has been trained to generate images of size 512x512.</li> <li>SDXL Turbo is open-access, but not open-source meaning that one might have to buy a model license in order to use it for commercial applications. 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