diffusers/pr_10167/en/_app/immutable/nodes/174.fb6fa448.js

import{s as G,n as V,o as Y}from"../chunks/scheduler.8c3d61f6.js";import{S as B,i as F,g as d,s as r,r as z,A as J,h as f,f as a,c as n,j as U,x as v,u as A,k as M,y as K,a as i,v as I,d as O,t as R,w as W}from"../chunks/index.da70eac4.js";import{H as N,E as Q}from"../chunks/EditOnGithub.1e64e623.js";function X(C){let s,w,g,y,o,D='<br/> <img src="https://raw.githubusercontent.com/huggingface/diffusers/77aadfee6a891ab9fcfb780f87c693f7a5beeb8e/docs/source/imgs/diffusers_library.jpg" width="400"/> <br/>',x,u,_,p,E='🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you’re looking for a simple inference solution or want to train your own diffusion model, 🤗 Diffusers is a modular toolbox that supports both. Our library is designed with a focus on <a href="conceptual/philosophy#usability-over-performance">usability over performance</a>, <a href="conceptual/philosophy#simple-over-easy">simple over easy</a>, and <a href="conceptual/philosophy#tweakable-contributorfriendly-over-abstraction">customizability over abstractions</a>.',$,c,j="The library has three main components:",k,h,S='<li>State-of-the-art diffusion pipelines for inference with just a few lines of code. There are many pipelines in 🤗 Diffusers, check out the table in the pipeline <a href="api/pipelines/overview">overview</a> for a complete list of available pipelines and the task they solve.</li> <li>Interchangeable <a href="api/schedulers/overview">noise schedulers</a> for balancing trade-offs between generation speed and quality.</li> <li>Pretrained <a href="api/models">models</a> that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.</li>',T,l,q='<div class="w-full flex flex-col space-y-4 md:space-y-0 md:grid md:grid-cols-2 md:gap-y-4 md:gap-x-5"><a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./tutorials/tutorial_overview"><div class="w-full text-center bg-gradient-to-br from-blue-400 to-blue-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">Tutorials</div> <p class="text-gray-700">Learn the fundamental skills you need to start generating outputs, build your own diffusion system, and train a diffusion model. We recommend starting here if you&#39;re using 🤗 Diffusers for the first time!</p></a> <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./using-diffusers/loading_overview"><div class="w-full text-center bg-gradient-to-br from-indigo-400 to-indigo-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">How-to guides</div> <p class="text-gray-700">Practical guides for helping you load pipelines, models, and schedulers. You&#39;ll also learn how to use pipelines for specific tasks, control how outputs are generated, optimize for inference speed, and different training techniques.</p></a> <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./conceptual/philosophy"><div class="w-full text-center bg-gradient-to-br from-pink-400 to-pink-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">Conceptual guides</div> <p class="text-gray-700">Understand why the library was designed the way it was, and learn more about the ethical guidelines and safety implementations for using the library.</p></a> <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./api/models/overview"><div class="w-full text-center bg-gradient-to-br from-purple-400 to-purple-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">Reference</div> <p class="text-gray-700">Technical descriptions of how 🤗 Diffusers classes and methods work.</p></a></div>',H,m,L,b,P;return u=new N({props:{title:"Diffusers",local:"diffusers",headingTag:"h1"}}),m=new Q({props:{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/en/index.md"}}),{c(){s=d("meta"),w=r(),g=d("p"),y=r(),o=d("p"),o.innerHTML=D,x=r(),z(u.$$.fragment),_=r(),p=d("p"),p.innerHTML=E,$=r(),c=d("p"),c.textContent=j,k=r(),h=d("ul"),h.innerHTML=S,T=r(),l=d("div"),l.innerHTML=q,H=r(),z(m.$$.fragment),L=r(),b=d("p"),this.h()},l(e){const t=J("svelte-u9bgzb",document.head);s=f(t,"META",{name:!0,content:!0}),t.forEach(a),w=n(e),g=f(e,"P",{}),U(g).forEach(a),y=n(e),o=f(e,"P",{align:!0,"data-svelte-h":!0}),v(o)!=="svelte-aksdn0"&&(o.innerHTML=D),x=n(e),A(u.$$.fragment,e),_=n(e),p=f(e,"P",{"data-svelte-h":!0}),v(p)!=="svelte-1vpau65"&&(p.innerHTML=E),$=n(e),c=f(e,"P",{"data-svelte-h":!0}),v(c)!=="svelte-1jx59eh"&&(c.textContent=j),k=n(e),h=f(e,"UL",{"data-svelte-h":!0}),v(h)!=="svelte-1i3mop4"&&(h.innerHTML=S),T=n(e),l=f(e,"DIV",{class:!0,"data-svelte-h":!0}),v(l)!=="svelte-1cp7snl"&&(l.innerHTML=q),H=n(e),A(m.$$.fragment,e),L=n(e),b=f(e,"P",{}),U(b).forEach(a),this.h()},h(){M(s,"name","hf:doc:metadata"),M(s,"content",Z),M(o,"align","center"),M(l,"class","mt-10")},m(e,t){K(document.head,s),i(e,w,t),i(e,g,t),i(e,y,t),i(e,o,t),i(e,x,t),I(u,e,t),i(e,_,t),i(e,p,t),i(e,$,t),i(e,c,t),i(e,k,t),i(e,h,t),i(e,T,t),i(e,l,t),i(e,H,t),I(m,e,t),i(e,L,t),i(e,b,t),P=!0},p:V,i(e){P||(O(u.$$.fragment,e),O(m.$$.fragment,e),P=!0)},o(e){R(u.$$.fragment,e),R(m.$$.fragment,e),P=!1},d(e){e&&(a(w),a(g),a(y),a(o),a(x),a(_),a(p),a($),a(c),a(k),a(h),a(T),a(l),a(H),a(L),a(b)),a(s),W(u,e),W(m,e)}}}const Z='{"title":"Diffusers","local":"diffusers","sections":[],"depth":1}';function ee(C){return Y(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class se extends B{constructor(s){super(),F(this,s,ee,X,G,{})}}export{se as component};