Buckets:
| import{s as me,n as pe,o as ce}from"../chunks/scheduler.f3b1e791.js";import{S as ue,i as de,e as i,s as a,c as k,h as fe,a as r,d as n,b as s,f as ee,g as M,j as v,k as P,l as W,m as l,n as L,t as x,o as J,p as _}from"../chunks/index.023a9934.js";import{C as he}from"../chunks/CopyLLMTxtMenu.c780467c.js";import{C as F}from"../chunks/CodeBlock.fc650646.js";import{H as we,E as $e}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.fb377ec3.js";function ge(te){let m,q,I,B,u,E,d,z,o,C,ne=`<code>kernels</code> has not reached <code>1.0</code> yet. Until then, minor releases may contain | |
| breaking changes. If you depend on <code>kernels</code> in a library or application, we | |
| <strong>strongly recommend pinning a version range</strong> rather than an unbounded | |
| dependency. For example, in <code>pyproject.toml</code>:`,K,f,Y,H,le=`or equivalently <code>kernels~=0.15</code> (compatible release). This protects your | |
| project from unexpected breakage when a new <code>kernels</code> version is released.`,G,h,ae="Install the <code>kernels</code> package with <code>pip</code> (requires <code>torch>=2.5</code> and CUDA):",S,w,A,$,se="or with <code>uv</code>",R,g,Z,b,oe="or if you want the latest version from the <code>main</code> branch:",O,T,V,p,ie=`<p>On Windows, we recommend using the Linux version of Torch through | |
| <a href="https://learn.microsoft.com/en-us/windows/wsl/install" rel="nofollow">WSL 2</a>, since | |
| many more kernels support Linux. If you want to use GPU acceleration, | |
| check out the <a href="https://docs.nvidia.com/cuda/wsl-user-guide/index.html#getting-started-with-cuda-on-wsl-2" rel="nofollow">CUDA on WSL</a> | |
| and <a href="https://learn.microsoft.com/en-us/windows/ai/directml/pytorch-wsl" rel="nofollow">PyTorch with DirectML on WSL 2</a> | |
| guides.</p>`,D,c,re=`<p>We strongly recommend not using a free-threaded Python build yet. | |
| These builds are not only experimental, but do not support the stable ABI | |
| on Python versions before 3.15. Kernels are compiled with the stable ABI | |
| to support a wide range of Python versions.</p>`,N,y,Q,j,X;return u=new he({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),d=new we({props:{title:"Installation",local:"installation",headingTag:"h1"}}),f=new F({props:{code:"ZGVwZW5kZW5jaWVzJTIwJTNEJTIwJTVCJTBBJTIwJTIwJTIwJTIwJTIya2VybmVscyUzRSUzRDAuMTUlMkMlM0MwLjE2JTIyJTJDJTBBJTVE",highlighted:`<span class="hljs-attr">dependencies</span> = [ | |
| <span class="hljs-string">"kernels>=0.15,<0.16"</span>, | |
| ]`,lang:"toml",wrap:!1}}),w=new F({props:{code:"cGlwJTIwaW5zdGFsbCUyMGtlcm5lbHM=",highlighted:"pip install kernels",lang:"bash",wrap:!1}}),g=new F({props:{code:"dXYlMjBwaXAlMjBpbnN0YWxsJTIwa2VybmVscw==",highlighted:"uv pip install kernels",lang:"bash",wrap:!1}}),T=new F({props:{code:"cGlwJTIwaW5zdGFsbCUyMCUyMmtlcm5lbHMlNUJiZW5jaG1hcmslNUQlMjAlNDAlMjBnaXQlMkJodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZodWdnaW5nZmFjZSUyRmtlcm5lbHMlMjNzdWJkaXJlY3RvcnklM0RrZXJuZWxzJTIy",highlighted:'pip install <span class="hljs-string">"kernels[benchmark] @ git+https://github.com/huggingface/kernels#subdirectory=kernels"</span>',lang:"bash",wrap:!1}}),y=new $e({props:{source:"https://github.com/huggingface/kernels/blob/main/docs/source/installation.md"}}),{c(){m=i("meta"),q=a(),I=i("p"),B=a(),k(u.$$.fragment),E=a(),k(d.$$.fragment),z=a(),o=i("blockquote"),C=i("p"),C.innerHTML=ne,K=a(),k(f.$$.fragment),Y=a(),H=i("p"),H.innerHTML=le,G=a(),h=i("p"),h.innerHTML=ae,S=a(),k(w.$$.fragment),A=a(),$=i("p"),$.innerHTML=se,R=a(),k(g.$$.fragment),Z=a(),b=i("p"),b.innerHTML=oe,O=a(),k(T.$$.fragment),V=a(),p=i("blockquote"),p.innerHTML=ie,D=a(),c=i("blockquote"),c.innerHTML=re,N=a(),k(y.$$.fragment),Q=a(),j=i("p"),this.h()},l(e){const t=fe("svelte-u9bgzb",document.head);m=r(t,"META",{name:!0,content:!0}),t.forEach(n),q=s(e),I=r(e,"P",{}),ee(I).forEach(n),B=s(e),M(u.$$.fragment,e),E=s(e),M(d.$$.fragment,e),z=s(e),o=r(e,"BLOCKQUOTE",{class:!0});var U=ee(o);C=r(U,"P",{"data-svelte-h":!0}),v(C)!=="svelte-6emakj"&&(C.innerHTML=ne),K=s(U),M(f.$$.fragment,U),Y=s(U),H=r(U,"P",{"data-svelte-h":!0}),v(H)!=="svelte-12c2da2"&&(H.innerHTML=le),U.forEach(n),G=s(e),h=r(e,"P",{"data-svelte-h":!0}),v(h)!=="svelte-1wkb7xn"&&(h.innerHTML=ae),S=s(e),M(w.$$.fragment,e),A=s(e),$=r(e,"P",{"data-svelte-h":!0}),v($)!=="svelte-oie08r"&&($.innerHTML=se),R=s(e),M(g.$$.fragment,e),Z=s(e),b=r(e,"P",{"data-svelte-h":!0}),v(b)!=="svelte-1wu94em"&&(b.innerHTML=oe),O=s(e),M(T.$$.fragment,e),V=s(e),p=r(e,"BLOCKQUOTE",{class:!0,"data-svelte-h":!0}),v(p)!=="svelte-115glw4"&&(p.innerHTML=ie),D=s(e),c=r(e,"BLOCKQUOTE",{class:!0,"data-svelte-h":!0}),v(c)!=="svelte-nce4hr"&&(c.innerHTML=re),N=s(e),M(y.$$.fragment,e),Q=s(e),j=r(e,"P",{}),ee(j).forEach(n),this.h()},h(){P(m,"name","hf:doc:metadata"),P(m,"content",be),P(o,"class","warning"),P(p,"class","important"),P(c,"class","important")},m(e,t){W(document.head,m),l(e,q,t),l(e,I,t),l(e,B,t),L(u,e,t),l(e,E,t),L(d,e,t),l(e,z,t),l(e,o,t),W(o,C),W(o,K),L(f,o,null),W(o,Y),W(o,H),l(e,G,t),l(e,h,t),l(e,S,t),L(w,e,t),l(e,A,t),l(e,$,t),l(e,R,t),L(g,e,t),l(e,Z,t),l(e,b,t),l(e,O,t),L(T,e,t),l(e,V,t),l(e,p,t),l(e,D,t),l(e,c,t),l(e,N,t),L(y,e,t),l(e,Q,t),l(e,j,t),X=!0},p:pe,i(e){X||(x(u.$$.fragment,e),x(d.$$.fragment,e),x(f.$$.fragment,e),x(w.$$.fragment,e),x(g.$$.fragment,e),x(T.$$.fragment,e),x(y.$$.fragment,e),X=!0)},o(e){J(u.$$.fragment,e),J(d.$$.fragment,e),J(f.$$.fragment,e),J(w.$$.fragment,e),J(g.$$.fragment,e),J(T.$$.fragment,e),J(y.$$.fragment,e),X=!1},d(e){e&&(n(q),n(I),n(B),n(E),n(z),n(o),n(G),n(h),n(S),n(A),n($),n(R),n(Z),n(b),n(O),n(V),n(p),n(D),n(c),n(N),n(Q),n(j)),n(m),_(u,e),_(d,e),_(f),_(w,e),_(g,e),_(T,e),_(y,e)}}}const be='{"title":"Installation","local":"installation","sections":[],"depth":1}';function Te(te){return ce(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class xe extends ue{constructor(m){super(),de(this,m,Te,ge,me,{})}}export{xe as component}; | |
Xet Storage Details
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- 5.96 kB
- Xet hash:
- 03fdefe3a75c220943155311ac23f8436df7605ce8b8e4e4451a6bdc17e7939d
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Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.