Buckets:

HuggingFaceDocBuilder's picture
download
raw
4.8 kB
import{s as Q,n as X,o as Z}from"../chunks/scheduler.f3b1e791.js";import{S as ee,i as te,e as i,s as l,c as j,h as ne,a as r,d as n,b as s,f as J,g as A,j as v,k as S,l as ae,m as a,n as q,t as B,o as I,p as D}from"../chunks/index.023a9934.js";import{C as le}from"../chunks/CopyLLMTxtMenu.3d5c1b04.js";import{H as se,E as ie}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.ea848e0a.js";function re(F){let o,_,$,H,m,T,c,x,u,O='<a href="https://huggingface.co/kernels"><img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/kernels/kernels-thumbnail-light.png" alt="Kernels"/> <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/kernels/kernels-thumbnail-dark.png" alt="Kernels"/></a>',w,p,R=`The Kernel Hub allows Python libraries and applications to load compute
kernels directly from the <a href="https://huggingface.co/" rel="nofollow">Hub</a>. Kernels are a first-class
repository type on the Hub, with dedicated pages that surface supported
hardware and versions. To support dynamic loading, Hub kernels differ from
traditional Python kernel packages in that they are made to be:`,P,d,G=`<li><strong>Portable</strong>: a kernel can be loaded from paths outside <code>PYTHONPATH</code>.</li> <li><strong>Unique</strong>: multiple versions of the same kernel can be loaded in the
same Python process.</li> <li><strong>Compatible</strong>: <code>kernels</code> must support all recent versions of Python and
the different PyTorch build configurations (various CUDA versions
and C++ ABIs). Furthermore, older C library versions must be supported.</li>`,L,f,N='Browse available kernels at <a href="https://huggingface.co/kernels" rel="nofollow">huggingface.co/kernels</a>.',C,h,V="The Kernels project is divided into two parts:",M,g,W=`<li>Builder: <a href="../source/builder-cli"><code>kernel-builder</code></a> provides utilities to build, package, and distribute compute kernels in a way that is compatible with the Hugging Face Hub and <code>kernels</code>.</li> <li><code>kernels</code>: The <a href="../source/basic-usage"><code>kernels</code></a> is a Python package that lets
users load compatible compute kernels from the Hub. Refer to the <a href="../source/basic-usage">quickstart</a> to know more.</li>`,K,k,Y=`If you’re looking for a more involved “Why kernels?” answer, refer to
<a href="./why_kernels">this page</a>.`,E,b,z,y,U;return m=new le({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),c=new se({props:{title:"Kernels",local:"kernels",headingTag:"h1"}}),b=new ie({props:{source:"https://github.com/huggingface/kernels/blob/main/docs/source/index.md"}}),{c(){o=i("meta"),_=l(),$=i("p"),H=l(),j(m.$$.fragment),T=l(),j(c.$$.fragment),x=l(),u=i("div"),u.innerHTML=O,w=l(),p=i("p"),p.innerHTML=R,P=l(),d=i("ul"),d.innerHTML=G,L=l(),f=i("p"),f.innerHTML=N,C=l(),h=i("p"),h.textContent=V,M=l(),g=i("ul"),g.innerHTML=W,K=l(),k=i("p"),k.innerHTML=Y,E=l(),j(b.$$.fragment),z=l(),y=i("p"),this.h()},l(e){const t=ne("svelte-u9bgzb",document.head);o=r(t,"META",{name:!0,content:!0}),t.forEach(n),_=s(e),$=r(e,"P",{}),J($).forEach(n),H=s(e),A(m.$$.fragment,e),T=s(e),A(c.$$.fragment,e),x=s(e),u=r(e,"DIV",{align:!0,"data-svelte-h":!0}),v(u)!=="svelte-1s7pjo"&&(u.innerHTML=O),w=s(e),p=r(e,"P",{"data-svelte-h":!0}),v(p)!=="svelte-d2zfnz"&&(p.innerHTML=R),P=s(e),d=r(e,"UL",{"data-svelte-h":!0}),v(d)!=="svelte-x1puvx"&&(d.innerHTML=G),L=s(e),f=r(e,"P",{"data-svelte-h":!0}),v(f)!=="svelte-5afj4y"&&(f.innerHTML=N),C=s(e),h=r(e,"P",{"data-svelte-h":!0}),v(h)!=="svelte-mh7hht"&&(h.textContent=V),M=s(e),g=r(e,"UL",{"data-svelte-h":!0}),v(g)!=="svelte-hr20vt"&&(g.innerHTML=W),K=s(e),k=r(e,"P",{"data-svelte-h":!0}),v(k)!=="svelte-msuz7s"&&(k.innerHTML=Y),E=s(e),A(b.$$.fragment,e),z=s(e),y=r(e,"P",{}),J(y).forEach(n),this.h()},h(){S(o,"name","hf:doc:metadata"),S(o,"content",oe),S(u,"align","center")},m(e,t){ae(document.head,o),a(e,_,t),a(e,$,t),a(e,H,t),q(m,e,t),a(e,T,t),q(c,e,t),a(e,x,t),a(e,u,t),a(e,w,t),a(e,p,t),a(e,P,t),a(e,d,t),a(e,L,t),a(e,f,t),a(e,C,t),a(e,h,t),a(e,M,t),a(e,g,t),a(e,K,t),a(e,k,t),a(e,E,t),q(b,e,t),a(e,z,t),a(e,y,t),U=!0},p:X,i(e){U||(B(m.$$.fragment,e),B(c.$$.fragment,e),B(b.$$.fragment,e),U=!0)},o(e){I(m.$$.fragment,e),I(c.$$.fragment,e),I(b.$$.fragment,e),U=!1},d(e){e&&(n(_),n($),n(H),n(T),n(x),n(u),n(w),n(p),n(P),n(d),n(L),n(f),n(C),n(h),n(M),n(g),n(K),n(k),n(E),n(z),n(y)),n(o),D(m,e),D(c,e),D(b,e)}}}const oe='{"title":"Kernels","local":"kernels","sections":[],"depth":1}';function ue(F){return Z(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class fe extends ee{constructor(o){super(),te(this,o,ue,re,Q,{})}}export{fe as component};

Xet Storage Details

Size:
4.8 kB
·
Xet hash:
236fc172fe663fe8a0e48fe7f66e0e8c337e11f91b00c65cb75e6fdbb3e89188

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.