bitsandbytes/pr_1957/en/_app/immutable/nodes/9.81eb3318.js

import{s as el,c as Yl,u as zl,g as Ql,a as Dl,d as Fl,j as qe,o as El,n as St}from"../chunks/scheduler.8a2cc2fa.js";import{S as ll,i as nl,e as g,s as d,a as y,f as Yt,d as l,b as p,k as H,m as i,t as $,o as w,B as Ol,r as ql,u as Kl,l as tl,q as tn,v as en,w as Al,z as ln,x as nn,c as T,h as sn,g as C,j as M,n as U,p as v}from"../chunks/index.7079e750.js";import{C as on,H as j,E as an}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.b4e6c7b3.js";import{C as k}from"../chunks/CodeBlock.f363c474.js";import{e as Pl}from"../chunks/each.e59479a4.js";import{w as rn}from"../chunks/index.ed040676.js";const Vt=rn({});function mn(h,n){const u=new URL(window.location.href),e=new URLSearchParams(u.search);e.set(h,n),u.search=e.toString(),history.replaceState(null,"",u.toString())}function dn(h){const n=new URL(window.location.href);return new URLSearchParams(n.search).get(h)}function Sl(h,n,u){const e=h.slice();return e[7]=n[u],e}function Xl(h){let n,u=h[7]+"",e,a,r,f,m;function c(){return h[6](h[7])}return{c(){n=g("div"),e=ql(u),a=d(),this.h()},l(o){n=y(o,"DIV",{class:!0});var b=Yt(n);e=Kl(b,u),a=p(b),b.forEach(l),this.h()},h(){H(n,"class",r="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd "+(h[2][h[0]]===h[7]?"border-gray-800 bg-black dark:bg-gray-700 text-white":"text-gray-500 cursor-pointer opacity-90 hover:text-gray-700 dark:hover:text-gray-200 hover:shadow-sm"))},m(o,b){i(o,n,b),tl(n,e),tl(n,a),f||(m=tn(n,"click",c),f=!0)},p(o,b){h=o,b&2&&u!==(u=h[7]+"")&&en(e,u),b&7&&r!==(r="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd "+(h[2][h[0]]===h[7]?"border-gray-800 bg-black dark:bg-gray-700 text-white":"text-gray-500 cursor-pointer opacity-90 hover:text-gray-700 dark:hover:text-gray-200 hover:shadow-sm"))&&H(n,"class",r)},d(o){o&&l(n),f=!1,m()}}}function pn(h){let n,u,e,a,r=Pl(h[1]),f=[];for(let o=0;o<r.length;o+=1)f[o]=Xl(Sl(h,r,o));const m=h[5].default,c=Yl(m,h,h[4],null);return{c(){n=g("div");for(let o=0;o<f.length;o+=1)f[o].c();u=d(),e=g("div"),c&&c.c(),this.h()},l(o){n=y(o,"DIV",{class:!0});var b=Yt(n);for(let R=0;R<f.length;R+=1)f[R].l(b);b.forEach(l),u=p(o),e=y(o,"DIV",{class:!0});var J=Yt(e);c&&c.l(J),J.forEach(l),this.h()},h(){H(n,"class","flex space-x-2 items-center my-1.5 mr-8 h-7 !pl-0 -mx-3 md:mx-0"),H(e,"class","language-select")},m(o,b){i(o,n,b);for(let J=0;J<f.length;J+=1)f[J]&&f[J].m(n,null);i(o,u,b),i(o,e,b),c&&c.m(e,null),a=!0},p(o,[b]){if(b&15){r=Pl(o[1]);let J;for(J=0;J<r.length;J+=1){const R=Sl(o,r,J);f[J]?f[J].p(R,b):(f[J]=Xl(R),f[J].c(),f[J].m(n,null))}for(;J<f.length;J+=1)f[J].d(1);f.length=r.length}c&&c.p&&(!a||b&16)&&zl(c,m,o,o[4],a?Dl(m,o[4],b,null):Ql(o[4]),null)},i(o){a||($(c,o),a=!0)},o(o){w(c,o),a=!1},d(o){o&&(l(n),l(u),l(e)),Ol(f,o),c&&c.d(o)}}}function un(h,n,u){let e;Fl(h,Vt,b=>u(2,e=b));let{$$slots:a={},$$scope:r}=n,{id:f}=n,{options:m}=n;qe(Vt,e[f]=m[0],e);function c(b){qe(Vt,e[f]=b,e),mn(f,b)}El(()=>{const b=dn(f);b&&m.includes(b)&&qe(Vt,e[f]=b,e)});const o=b=>c(b);return h.$$set=b=>{"id"in b&&u(0,f=b.id),"options"in b&&u(1,m=b.options),"$$scope"in b&&u(4,r=b.$$scope)},[f,m,e,c,r,a,o]}class Ke extends ll{constructor(n){super(),nl(this,n,un,pn,el,{id:0,options:1})}}function Vl(h){let n;const u=h[4].default,e=Yl(u,h,h[3],null);return{c(){e&&e.c()},l(a){e&&e.l(a)},m(a,r){e&&e.m(a,r),n=!0},p(a,r){e&&e.p&&(!n||r&8)&&zl(e,u,a,a[3],n?Dl(u,a[3],r,null):Ql(a[3]),null)},i(a){n||($(e,a),n=!0)},o(a){w(e,a),n=!1},d(a){e&&e.d(a)}}}function fn(h){let n,u,e=h[2][h[0]]===h[1]&&Vl(h);return{c(){e&&e.c(),n=Al()},l(a){e&&e.l(a),n=Al()},m(a,r){e&&e.m(a,r),i(a,n,r),u=!0},p(a,[r]){a[2][a[0]]===a[1]?e?(e.p(a,r),r&7&&$(e,1)):(e=Vl(a),e.c(),$(e,1),e.m(n.parentNode,n)):e&&(ln(),w(e,1,1,()=>{e=null}),nn())},i(a){u||($(e),u=!0)},o(a){w(e),u=!1},d(a){a&&l(n),e&&e.d(a)}}}function cn(h,n,u){let e;Fl(h,Vt,c=>u(2,e=c));let{$$slots:a={},$$scope:r}=n,{id:f}=n,{option:m}=n;return h.$$set=c=>{"id"in c&&u(0,f=c.id),"option"in c&&u(1,m=c.option),"$$scope"in c&&u(3,r=c.$$scope)},[f,m,e,r,a]}class Pt extends ll{constructor(n){super(),nl(this,n,cn,fn,el,{id:0,option:1})}}function hn(h){let n,u="To compile from source, you need CMake &gt;= <strong>3.22.1</strong> and Python &gt;= <strong>3.10</strong> installed. Make sure you have a compiler installed to compile C++ (<code>gcc</code>, <code>make</code>, headers, etc.). It is recommended to use GCC 11 or newer.",e,a,r="For example, to install a compiler and CMake on Ubuntu:",f,m,c,o,b='You should also install CUDA Toolkit by following the <a href="https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html" rel="nofollow">NVIDIA CUDA Installation Guide for Linux</a> guide. The current minimum supported CUDA Toolkit version that we support is <strong>11.8</strong>.',J,R,N,L,G="<p>If you have multiple versions of the CUDA Toolkit installed or it is in a non-standard location, please refer to CMake CUDA documentation for how to configure the CUDA compiler.</p>",_;return m=new k({props:{code:"YXB0LWdldCUyMGluc3RhbGwlMjAteSUyMGJ1aWxkLWVzc2VudGlhbCUyMGNtYWtl",highlighted:"apt-get install -y build-essential cmake",lang:"bash",wrap:!1}}),R=new k({props:{code:"Z2l0JTIwY2xvbmUlMjBodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZiaXRzYW5kYnl0ZXMtZm91bmRhdGlvbiUyRmJpdHNhbmRieXRlcy5naXQlMjAlMjYlMjYlMjBjZCUyMGJpdHNhbmRieXRlcyUyRiUwQWNtYWtlJTIwLURDT01QVVRFX0JBQ0tFTkQlM0RjdWRhJTIwLVMlMjAuJTBBbWFrZSUwQXBpcCUyMGluc3RhbGwlMjAtZSUyMC4lMjAlMjAlMjAlMjMlMjAlNjAtZSU2MCUyMGZvciUyMCUyMmVkaXRhYmxlJTIyJTIwaW5zdGFsbCUyQyUyMHdoZW4lMjBkZXZlbG9waW5nJTIwQk5CJTIwKG90aGVyd2lzZSUyMGxlYXZlJTIwdGhhdCUyMG91dCk=",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/bitsandbytes-foundation/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/
cmake -DCOMPUTE_BACKEND=cuda -S .
make
pip install -e .   <span class="hljs-comment"># \`-e\` for &quot;editable&quot; install, when developing BNB (otherwise leave that out)</span>`,lang:"bash",wrap:!1}}),{c(){n=g("p"),n.innerHTML=u,e=d(),a=g("p"),a.textContent=r,f=d(),T(m.$$.fragment),c=d(),o=g("p"),o.innerHTML=b,J=d(),T(R.$$.fragment),N=d(),L=g("blockquote"),L.innerHTML=G,this.h()},l(x){n=y(x,"P",{"data-svelte-h":!0}),M(n)!=="svelte-62t1s"&&(n.innerHTML=u),e=p(x),a=y(x,"P",{"data-svelte-h":!0}),M(a)!=="svelte-noyxvz"&&(a.textContent=r),f=p(x),C(m.$$.fragment,x),c=p(x),o=y(x,"P",{"data-svelte-h":!0}),M(o)!=="svelte-kc1jbt"&&(o.innerHTML=b),J=p(x),C(R.$$.fragment,x),N=p(x),L=y(x,"BLOCKQUOTE",{class:!0,"data-svelte-h":!0}),M(L)!=="svelte-1ayoph"&&(L.innerHTML=G),this.h()},h(){H(L,"class","tip")},m(x,I){i(x,n,I),i(x,e,I),i(x,a,I),i(x,f,I),U(m,x,I),i(x,c,I),i(x,o,I),i(x,J,I),U(R,x,I),i(x,N,I),i(x,L,I),_=!0},p:St,i(x){_||($(m.$$.fragment,x),$(R.$$.fragment,x),_=!0)},o(x){w(m.$$.fragment,x),w(R.$$.fragment,x),_=!1},d(x){x&&(l(n),l(e),l(a),l(f),l(c),l(o),l(J),l(N),l(L)),v(m,x),v(R,x)}}}function bn(h){let n,u="Compilation from source on Windows systems require Visual Studio with C++ support as well as an installation of the CUDA Toolkit.",e,a,r='To compile from source, you need CMake &gt;= <strong>3.22.1</strong> and Python &gt;= <strong>3.10</strong> installed. You should also install CUDA Toolkit by following the <a href="https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html" rel="nofollow">CUDA Installation Guide for Windows</a> guide from NVIDIA. The current minimum supported CUDA Toolkit version that we support is <strong>11.8</strong>.',f,m,c,o,b=`<p>If your locally built CUDA toolkit version does not match the CUDA version bundled with your PyTorch wheel, bitsandbytes may still try to load the PyTorch-matched binary name first.
On Windows, you can point bitsandbytes at your locally built DLL for the current shell with:
<code>set BNB_CUDA_VERSION=&lt;cuda-version-without-dots&gt;</code>
For example, a local CUDA 13.2 build uses <code>set BNB_CUDA_VERSION=132</code>.</p>`,J,R,N='Big thanks to <a href="https://github.com/wkpark" rel="nofollow">wkpark</a>, <a href="https://github.com/Jamezo97" rel="nofollow">Jamezo97</a>, <a href="https://github.com/rickardp" rel="nofollow">rickardp</a>, <a href="https://github.com/akx" rel="nofollow">akx</a> for their amazing contributions to make bitsandbytes compatible with Windows.',L;return m=new k({props:{code:"Z2l0JTIwY2xvbmUlMjBodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZiaXRzYW5kYnl0ZXMtZm91bmRhdGlvbiUyRmJpdHNhbmRieXRlcy5naXQlMjAlMjYlMjYlMjBjZCUyMGJpdHNhbmRieXRlcyUyRiUwQWNtYWtlJTIwLURDT01QVVRFX0JBQ0tFTkQlM0RjdWRhJTIwLVMlMjAuJTBBY21ha2UlMjAtLWJ1aWxkJTIwLiUyMC0tY29uZmlnJTIwUmVsZWFzZSUwQXBpcCUyMGluc3RhbGwlMjAtZSUyMC4lMjAlMjAlMjAlMjMlMjAlNjAtZSU2MCUyMGZvciUyMCUyMmVkaXRhYmxlJTIyJTIwaW5zdGFsbCUyQyUyMHdoZW4lMjBkZXZlbG9waW5nJTIwQk5CJTIwKG90aGVyd2lzZSUyMGxlYXZlJTIwdGhhdCUyMG91dCk=",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/bitsandbytes-foundation/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/
cmake -DCOMPUTE_BACKEND=cuda -S .
cmake --build . --config Release
pip install -e .   <span class="hljs-comment"># \`-e\` for &quot;editable&quot; install, when developing BNB (otherwise leave that out)</span>`,lang:"bash",wrap:!1}}),{c(){n=g("p"),n.textContent=u,e=d(),a=g("p"),a.innerHTML=r,f=d(),T(m.$$.fragment),c=d(),o=g("blockquote"),o.innerHTML=b,J=d(),R=g("p"),R.innerHTML=N,this.h()},l(G){n=y(G,"P",{"data-svelte-h":!0}),M(n)!=="svelte-10x6whz"&&(n.textContent=u),e=p(G),a=y(G,"P",{"data-svelte-h":!0}),M(a)!=="svelte-dit2ws"&&(a.innerHTML=r),f=p(G),C(m.$$.fragment,G),c=p(G),o=y(G,"BLOCKQUOTE",{class:!0,"data-svelte-h":!0}),M(o)!=="svelte-la4cgr"&&(o.innerHTML=b),J=p(G),R=y(G,"P",{"data-svelte-h":!0}),M(R)!=="svelte-e0ivb"&&(R.innerHTML=N),this.h()},h(){H(o,"class","tip")},m(G,_){i(G,n,_),i(G,e,_),i(G,a,_),i(G,f,_),U(m,G,_),i(G,c,_),i(G,o,_),i(G,J,_),i(G,R,_),L=!0},p:St,i(G){L||($(m.$$.fragment,G),L=!0)},o(G){w(m.$$.fragment,G),L=!1},d(G){G&&(l(n),l(e),l(a),l(f),l(c),l(o),l(J),l(R)),v(m,G)}}}function gn(h){let n,u,e,a;return n=new Pt({props:{id:"source",option:"Linux",$$slots:{default:[hn]},$$scope:{ctx:h}}}),e=new Pt({props:{id:"source",option:"Windows",$$slots:{default:[bn]},$$scope:{ctx:h}}}),{c(){T(n.$$.fragment),u=d(),T(e.$$.fragment)},l(r){C(n.$$.fragment,r),u=p(r),C(e.$$.fragment,r)},m(r,f){U(n,r,f),i(r,u,f),U(e,r,f),a=!0},p(r,f){const m={};f&2&&(m.$$scope={dirty:f,ctx:r}),n.$set(m);const c={};f&2&&(c.$$scope={dirty:f,ctx:r}),e.$set(c)},i(r){a||($(n.$$.fragment,r),$(e.$$.fragment,r),a=!0)},o(r){w(n.$$.fragment,r),w(e.$$.fragment,r),a=!1},d(r){r&&l(u),v(n,r),v(e,r)}}}function yn(h){let n,u="To compile from source, you need CMake &gt;= <strong>3.31.6</strong> and Python &gt;= <strong>3.10</strong> installed. Make sure you have a compiler installed to compile C++ (<code>gcc</code>, <code>make</code>, headers, etc.).",e,a,r="You should also have a ROCm installation (system-wide or via Docker). The current minimum supported version is <strong>6.2</strong>.",f,m,c;return m=new k({props:{code:"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",highlighted:`<span class="hljs-comment"># Install bitsandbytes from source</span>

<span class="hljs-comment"># Clone bitsandbytes repo</span>
git <span class="hljs-built_in">clone</span> https://github.com/bitsandbytes-foundation/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/

<span class="hljs-comment"># Compile &amp; install</span>
apt-get install -y build-essential cmake  <span class="hljs-comment"># install build tools dependencies, unless present</span>
cmake -DCOMPUTE_BACKEND=hip -S .  <span class="hljs-comment"># Use -DBNB_ROCM_ARCH=&quot;gfx90a;gfx942&quot; to target specific gpu arch</span>
make
pip install -e .   <span class="hljs-comment"># \`-e\` for &quot;editable&quot; install, when developing BNB (otherwise leave that out)</span>`,lang:"bash",wrap:!1}}),{c(){n=g("p"),n.innerHTML=u,e=d(),a=g("p"),a.innerHTML=r,f=d(),T(m.$$.fragment)},l(o){n=y(o,"P",{"data-svelte-h":!0}),M(n)!=="svelte-3khjtw"&&(n.innerHTML=u),e=p(o),a=y(o,"P",{"data-svelte-h":!0}),M(a)!=="svelte-1v5j4ex"&&(a.innerHTML=r),f=p(o),C(m.$$.fragment,o)},m(o,b){i(o,n,b),i(o,e,b),i(o,a,b),i(o,f,b),U(m,o,b),c=!0},p:St,i(o){c||($(m.$$.fragment,o),c=!0)},o(o){w(m.$$.fragment,o),c=!1},d(o){o&&(l(n),l(e),l(a),l(f)),v(m,o)}}}function Mn(h){let n,u="Compilation on Windows requires Visual Studio with C++ support, CMake, Ninja, and Python &gt;= <strong>3.10</strong>.",e,a,r='Instead of a system-wide ROCm installation, you can use the pip-installable ROCm SDK wheels from <a href="https://repo.radeon.com/rocm/windows/" rel="nofollow">repo.radeon.com</a>:',f,m,c;return m=new k({props:{code:"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",highlighted:`<span class="hljs-comment"># Install ROCm SDK wheels (adjust version as needed)</span>
pip install ninja cmake
pip install \\
    https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm_sdk_core-7.2.1-py3-none-win_amd64.whl \\
    https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm_sdk_devel-7.2.1-py3-none-win_amd64.whl \\
    https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm_sdk_libraries_custom-7.2.1-py3-none-win_amd64.whl \\
    https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm-7.2.1.tar.gz

<span class="hljs-comment"># Expand the devel tarball</span>
rocm-sdk init

<span class="hljs-comment"># Set ROCM_PATH and activate Visual Studio environment, then build</span>
<span class="hljs-built_in">export</span> ROCM_PATH=<span class="hljs-string">&quot;<span class="hljs-subst">$(rocm-sdk path --root)</span>&quot;</span>
<span class="hljs-built_in">export</span> PATH=<span class="hljs-string">&quot;<span class="hljs-variable">\${ROCM_PATH}</span>/bin:<span class="hljs-variable">\${PATH}</span>&quot;</span>
git <span class="hljs-built_in">clone</span> https://github.com/bitsandbytes-foundation/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/
cmake -G Ninja -DCOMPUTE_BACKEND=hip -DBNB_ROCM_ARCH=<span class="hljs-string">&quot;gfx1100&quot;</span> -DCMAKE_BUILD_TYPE=Release -S .
cmake --build . --config Release
pip install .`,lang:"bash",wrap:!1}}),{c(){n=g("p"),n.innerHTML=u,e=d(),a=g("p"),a.innerHTML=r,f=d(),T(m.$$.fragment)},l(o){n=y(o,"P",{"data-svelte-h":!0}),M(n)!=="svelte-12w6ctf"&&(n.innerHTML=u),e=p(o),a=y(o,"P",{"data-svelte-h":!0}),M(a)!=="svelte-13gc57q"&&(a.innerHTML=r),f=p(o),C(m.$$.fragment,o)},m(o,b){i(o,n,b),i(o,e,b),i(o,a,b),i(o,f,b),U(m,o,b),c=!0},p:St,i(o){c||($(m.$$.fragment,o),c=!0)},o(o){w(m.$$.fragment,o),c=!1},d(o){o&&(l(n),l(e),l(a),l(f)),v(m,o)}}}function $n(h){let n,u,e,a;return n=new Pt({props:{id:"rocm-source",option:"Linux",$$slots:{default:[yn]},$$scope:{ctx:h}}}),e=new Pt({props:{id:"rocm-source",option:"Windows",$$slots:{default:[Mn]},$$scope:{ctx:h}}}),{c(){T(n.$$.fragment),u=d(),T(e.$$.fragment)},l(r){C(n.$$.fragment,r),u=p(r),C(e.$$.fragment,r)},m(r,f){U(n,r,f),i(r,u,f),U(e,r,f),a=!0},p(r,f){const m={};f&2&&(m.$$scope={dirty:f,ctx:r}),n.$set(m);const c={};f&2&&(c.$$scope={dirty:f,ctx:r}),e.$set(c)},i(r){a||($(n.$$.fragment,r),$(e.$$.fragment,r),a=!0)},o(r){w(n.$$.fragment,r),w(e.$$.fragment,r),a=!1},d(r){r&&l(u),v(n,r),v(e,r)}}}function wn(h){let n,u;return n=new k({props:{code:"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",highlighted:`<span class="hljs-comment"># Note: if you don&#x27;t want to reinstall our dependencies, append the \`--no-deps\` flag!</span>

<span class="hljs-comment"># x86_64 (most users)</span>
pip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-manylinux_2_24_x86_64.whl

<span class="hljs-comment"># ARM/aarch64</span>
pip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-manylinux_2_24_aarch64.whl`,lang:"bash",wrap:!1}}),{c(){T(n.$$.fragment)},l(e){C(n.$$.fragment,e)},m(e,a){U(n,e,a),u=!0},p:St,i(e){u||($(n.$$.fragment,e),u=!0)},o(e){w(n.$$.fragment,e),u=!1},d(e){v(n,e)}}}function Tn(h){let n,u;return n=new k({props:{code:"JTIzJTIwTm90ZSUzQSUyMGlmJTIweW91JTIwZG9uJ3QlMjB3YW50JTIwdG8lMjByZWluc3RhbGwlMjBvdXIlMjBkZXBlbmRlbmNpZXMlMkMlMjBhcHBlbmQlMjB0aGUlMjAlNjAtLW5vLWRlcHMlNjAlMjBmbGFnISUwQXBpcCUyMGluc3RhbGwlMjAtLWZvcmNlLXJlaW5zdGFsbCUyMGh0dHBzJTNBJTJGJTJGZ2l0aHViLmNvbSUyRmJpdHNhbmRieXRlcy1mb3VuZGF0aW9uJTJGYml0c2FuZGJ5dGVzJTJGcmVsZWFzZXMlMkZkb3dubG9hZCUyRmNvbnRpbnVvdXMtcmVsZWFzZV9tYWluJTJGYml0c2FuZGJ5dGVzLTEuMzMuNy5wcmV2aWV3LXB5My1ub25lLXdpbl9hbWQ2NC53aGw=",highlighted:'<span class="hljs-comment"># Note: if you don&#x27;t want to reinstall our dependencies, append the `--no-deps` flag!</span>\npip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-win_amd64.whl',lang:"bash",wrap:!1}}),{c(){T(n.$$.fragment)},l(e){C(n.$$.fragment,e)},m(e,a){U(n,e,a),u=!0},p:St,i(e){u||($(n.$$.fragment,e),u=!0)},o(e){w(n.$$.fragment,e),u=!1},d(e){v(n,e)}}}function Cn(h){let n,u;return n=new k({props:{code:"JTIzJTIwTm90ZSUzQSUyMGlmJTIweW91JTIwZG9uJ3QlMjB3YW50JTIwdG8lMjByZWluc3RhbGwlMjBvdXIlMjBkZXBlbmRlbmNpZXMlMkMlMjBhcHBlbmQlMjB0aGUlMjAlNjAtLW5vLWRlcHMlNjAlMjBmbGFnISUwQXBpcCUyMGluc3RhbGwlMjAtLWZvcmNlLXJlaW5zdGFsbCUyMGh0dHBzJTNBJTJGJTJGZ2l0aHViLmNvbSUyRmJpdHNhbmRieXRlcy1mb3VuZGF0aW9uJTJGYml0c2FuZGJ5dGVzJTJGcmVsZWFzZXMlMkZkb3dubG9hZCUyRmNvbnRpbnVvdXMtcmVsZWFzZV9tYWluJTJGYml0c2FuZGJ5dGVzLTEuMzMuNy5wcmV2aWV3LXB5My1ub25lLW1hY29zeF8xNF8wX2FybTY0LndobA==",highlighted:'<span class="hljs-comment"># Note: if you don&#x27;t want to reinstall our dependencies, append the `--no-deps` flag!</span>\npip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-macosx_14_0_arm64.whl',lang:"bash",wrap:!1}}),{c(){T(n.$$.fragment)},l(e){C(n.$$.fragment,e)},m(e,a){U(n,e,a),u=!0},p:St,i(e){u||($(n.$$.fragment,e),u=!0)},o(e){w(n.$$.fragment,e),u=!1},d(e){v(n,e)}}}function Un(h){let n,u,e,a,r,f;return n=new Pt({props:{id:"OS",option:"Linux",$$slots:{default:[wn]},$$scope:{ctx:h}}}),e=new Pt({props:{id:"OS",option:"Windows",$$slots:{default:[Tn]},$$scope:{ctx:h}}}),r=new Pt({props:{id:"OS",option:"macOS",$$slots:{default:[Cn]},$$scope:{ctx:h}}}),{c(){T(n.$$.fragment),u=d(),T(e.$$.fragment),a=d(),T(r.$$.fragment)},l(m){C(n.$$.fragment,m),u=p(m),C(e.$$.fragment,m),a=p(m),C(r.$$.fragment,m)},m(m,c){U(n,m,c),i(m,u,c),U(e,m,c),i(m,a,c),U(r,m,c),f=!0},p(m,c){const o={};c&2&&(o.$$scope={dirty:c,ctx:m}),n.$set(o);const b={};c&2&&(b.$$scope={dirty:c,ctx:m}),e.$set(b);const J={};c&2&&(J.$$scope={dirty:c,ctx:m}),r.$set(J)},i(m){f||($(n.$$.fragment,m),$(e.$$.fragment,m),$(r.$$.fragment,m),f=!0)},o(m){w(n.$$.fragment,m),w(e.$$.fragment,m),w(r.$$.fragment,m),f=!1},d(m){m&&(l(u),l(a)),v(n,m),v(e,m),v(r,m)}}}function vn(h){let n,u,e,a,r,f,m,c,o,b="Welcome to the installation guide for the <code>bitsandbytes</code> library! This document provides step-by-step instructions to install <code>bitsandbytes</code> across various platforms and hardware configurations.",J,R,N="We provide official support for NVIDIA GPUs, CPUs, Intel XPUs, and Intel Gaudi. We also have experimental support for additional platforms such as AMD ROCm and Apple Silicon.",L,G,_,x,I='<li><a href="#requirements">System Requirements</a></li> <li><a href="#cuda">NVIDIA CUDA</a> <ul><li><a href="#cuda-pip">Installation via PyPI</a></li> <li><a href="#cuda-compile">Compile from Source</a></li></ul></li> <li><a href="#xpu">Intel XPU</a> <ul><li><a href="#xpu-pip">Installation via PyPI</a></li></ul></li> <li><a href="#gaudi">Intel Gaudi</a> <ul><li><a href="#gaudi-pip">Installation via PyPI</a></li></ul></li> <li><a href="#cpu">CPU</a> <ul><li><a href="#cpu-pip">Installation via PyPI</a></li> <li><a href="#cpu-compile">Compile from Source</a></li></ul></li> <li><a href="#rocm">AMD ROCm (Preview)</a> <ul><li><a href="#rocm-pip">Installation via PyPI</a></li> <li><a href="#rocm-compile">Compile from Source</a></li></ul></li> <li><a href="#preview-wheels">Preview Wheels</a></li>',zt,S,Qt,X,sl="These are the minimum requirements for <code>bitsandbytes</code> across all platforms. Please be aware that some compute platforms may impose more strict requirements.",Dt,V,il="<li>Python &gt;= 3.10</li> <li>PyTorch &gt;= 2.4</li>",Ft,Y,Et,z,ol=`<code>bitsandbytes</code> is currently supported on NVIDIA GPUs with <a href="https://developer.nvidia.com/cuda-gpus" rel="nofollow">Compute Capability</a> 6.0+.
The library can be built using CUDA Toolkit versions as old as <strong>11.8</strong>.`,Ot,Q,al="<thead><tr><th><strong>Feature</strong></th> <th><strong>CC Required</strong></th> <th><strong>Example Hardware Requirement</strong></th></tr></thead> <tbody><tr><td>LLM.int8()</td> <td>7.5+</td> <td>Turing (RTX 20 series, T4) or newer GPUs</td></tr> <tr><td>8-bit optimizers/quantization</td> <td>6.0+</td> <td>Pascal (GTX 10X0 series, P100) or newer GPUs</td></tr> <tr><td>NF4/FP4 quantization</td> <td>6.0+</td> <td>Pascal (GTX 10X0 series, P100) or newer GPUs</td></tr></tbody>",qt,D,Kt,F,rl="This is the most straightforward and recommended installation option.",te,E,ml="The currently distributed <code>bitsandbytes</code> packages are built with the following configurations:",ee,O,dl="<thead><tr><th><strong>OS</strong></th> <th><strong>CUDA Toolkit</strong></th> <th><strong>Host Compiler</strong></th> <th><strong>Targets</strong></th></tr></thead> <tbody><tr><td><strong>Linux x86-64</strong></td> <td>11.8 - 12.6</td> <td>GCC 11.2</td> <td>sm60, sm70, sm75, sm80, sm86, sm89, sm90</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>12.8 - 12.9</td> <td>GCC 11.2</td> <td>sm70, sm75, sm80, sm86, sm89, sm90, sm100, sm120</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>13.0</td> <td>GCC 11.2</td> <td>sm75, sm80, sm86, sm89, sm90, sm100, sm120</td></tr> <tr><td><strong>Linux aarch64</strong></td> <td>11.8 - 12.6</td> <td>GCC 11.2</td> <td>sm75, sm80, sm90</td></tr> <tr><td><strong>Linux aarch64</strong></td> <td>12.8 - 13.0</td> <td>GCC 11.2</td> <td>sm75, sm80, sm90, sm100, sm110, sm120, sm121</td></tr> <tr><td><strong>Windows x86-64</strong></td> <td>11.8 - 12.6</td> <td>MSVC 19.43+ (VS2022)</td> <td>sm50, sm60, sm75, sm80, sm86, sm89, sm90</td></tr> <tr><td><strong>Windows x86-64</strong></td> <td>12.8 - 12.9</td> <td>MSVC 19.43+ (VS2022)</td> <td>sm70, sm75, sm80, sm86, sm89, sm90, sm100, sm120</td></tr> <tr><td><strong>Windows x86-64</strong></td> <td>13.0</td> <td>MSVC 19.43+ (VS2022)</td> <td>sm75, sm80, sm86, sm89, sm90, sm100, sm120</td></tr></tbody>",le,q,pl="The Linux build has a minimum glibc version of 2.24.",ne,K,ul="Use <code>pip</code> or <code>uv</code> to install the latest release:",se,tt,ie,B,fl='<p><strong>NVIDIA Jetson (L4T / JetPack) — source build required.</strong> The <code>Linux aarch64</code> wheels above are built on aarch64-sbsa runners (server-class ARM with the standard CUDA Toolkit). They are <strong>not compatible</strong> with the L4T runtime on Jetson devices (Orin Nano / NX / AGX, Xavier, Thor on CUDA 12), even though both are aarch64 and even though the cubins are binary-compatible with the device’s compute capability (e.g., <code>sm_80</code> cubin runs on <code>sm_87</code> hardware via Ampere-family binary compat — see <a href="https://developer.nvidia.com/blog/understanding-ptx-the-assembly-language-of-cuda-gpu-computing/#binary_compatibility" rel="nofollow">NVIDIA’s docs on binary compatibility</a>). The mismatch is at the CUDA library / ABI layer (JetPack ships its own CUDA Toolkit and system libraries), and surfaces as a runtime symbol-resolution error like <code>Error named symbol not found in /src/csrc/ops.cu</code> on the first CUDA op.</p> <p><strong>Two working options on Jetson:</strong></p> <ol><li><strong>Source build on-device.</strong> Use the <a href="#cuda-compile">Compile from Source</a> instructions below, passing your device’s compute capability explicitly (sm_87 for Orin family, sm_72 for Xavier). On an Orin Nano Super: <code>cmake -DCOMPUTE_BACKEND=cuda -DCOMPUTE_CAPABILITY=87 . &amp;&amp; make -j4 &amp;&amp; pip install .</code></li> <li><strong>Third-party prebuilt</strong> from <a href="https://pypi.jetson-ai-lab.io/" rel="nofollow">Jetson AI Lab’s package index</a> (e.g., <code>pypi.jetson-ai-lab.io/jp6/cu126/bitsandbytes/</code>).</li></ol>',oe,et,ae,W,cl="<p>Don’t hesitate to compile from source! The process is pretty straight forward and resilient. This might be needed for older CUDA Toolkit versions or Linux distributions, or other less common configurations.</p>",re,lt,hl="For Linux and Windows systems, compiling from source allows you to customize the build configurations. See below for detailed platform-specific instructions (see the <code>CMakeLists.txt</code> if you want to check the specifics and explore some additional options):",me,Z,de,nt,pe,st,bl='<li>A compatible PyTorch version with Intel XPU support is required. The current minimum is <strong>PyTorch 2.6.0</strong>. It is recommended to use the latest stable release. See <a href="https://docs.pytorch.org/docs/stable/notes/get_start_xpu.html" rel="nofollow">Getting Started on Intel GPU</a> for guidance.</li>',ue,it,fe,ot,gl="This is the most straightforward and recommended installation option.",ce,at,yl="The currently distributed <code>bitsandbytes</code> packages are built with the following configurations:",he,rt,Ml="<thead><tr><th><strong>OS</strong></th> <th><strong>oneAPI Toolkit</strong></th> <th><strong>Kernel Implementation</strong></th></tr></thead> <tbody><tr><td><strong>Linux x86-64</strong></td> <td>2025.1.3</td> <td>SYCL + Triton</td></tr> <tr><td><strong>Windows x86-64</strong></td> <td>2025.1.3</td> <td>SYCL + Triton</td></tr></tbody>",be,mt,$l="The Linux build has a minimum glibc version of 2.34.",ge,dt,wl="Use <code>pip</code> or <code>uv</code> to install the latest release:",ye,pt,Me,ut,$e,ft,Tl='<li>A compatible PyTorch version with Intel Gaudi support is required. The current minimum is <strong>Gaudi v1.21</strong> with <strong>PyTorch 2.6.0</strong>. It is recommended to use the latest stable release. See the Gaudi software <a href="https://docs.habana.ai/en/latest/Installation_Guide/index.html" rel="nofollow">installation guide</a> for guidance.</li>',we,ct,Te,ht,Cl="Use <code>pip</code> or <code>uv</code> to install the latest release:",Ce,bt,Ue,gt,ve,yt,xe,Mt,Ul="This is the most straightforward and recommended installation option.",Je,$t,vl="The currently distributed <code>bitsandbytes</code> packages are built with the following configurations:",Ge,wt,xl="<thead><tr><th><strong>OS</strong></th> <th><strong>Host Compiler</strong></th> <th>Hardware Minimum</th></tr></thead> <tbody><tr><td><strong>Linux x86-64</strong></td> <td>GCC 11.4</td> <td>AVX2</td></tr> <tr><td><strong>Linux aarch64</strong></td> <td>GCC 11.4</td> <td></td></tr> <tr><td><strong>Windows x86-64</strong></td> <td>MSVC 19.43+ (VS2022)</td> <td>AVX2</td></tr> <tr><td><strong>macOS arm64</strong></td> <td>Apple Clang 17</td> <td></td></tr></tbody>",Re,Tt,Jl="The Linux build has a minimum glibc version of 2.24.",_e,Ct,Gl="Use <code>pip</code> or <code>uv</code> to install the latest release:",Le,Ut,je,vt,Ie,xt,Rl="To compile from source, simply install the package from source using <code>pip</code>. The package will be built for CPU only at this time.",ke,Jt,Ne,Gt,He,Rt,_l=`<li>Support for AMD GPUs is currently in a preview state.</li> <li>All features are supported for both consumer RDNA devices and Data Center CDNA products.</li> <li>A compatible PyTorch version with AMD ROCm support is required. It is recommended to use the latest stable release. On Linux, see <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html" rel="nofollow">PyTorch on ROCm</a> for guidance. On Windows, ROCm-enabled PyTorch wheels are available from:
<ul><li><a href="https://repo.radeon.com/rocm/windows/" rel="nofollow">repo.radeon.com/rocm/windows/</a> — official AMD releases</li> <li><a href="https://repo.amd.com/rocm/whl/" rel="nofollow">repo.amd.com/rocm/whl/</a> — <a href="https://github.com/ROCm/TheRock" rel="nofollow">TheRock</a> release builds</li> <li><a href="https://rocm.nightlies.amd.com/v2" rel="nofollow">rocm.nightlies.amd.com/v2</a> — TheRock nightly builds</li></ul></li>`,Be,_t,We,Lt,Ll="This is the most straightforward and recommended installation option.",Ze,jt,jl="The currently distributed <code>bitsandbytes</code> are built with the following configurations:",Ae,It,Il="<thead><tr><th><strong>OS</strong></th> <th><strong>ROCm</strong></th> <th><strong>Targets</strong></th></tr></thead> <tbody><tr><td><strong>Linux x86-64</strong></td> <td>6.2.4</td> <td>CDNA: gfx90a, gfx942 / RDNA: gfx1100, gfx1101, gfx1102, gfx1103</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>6.3.4</td> <td>CDNA: gfx90a, gfx942 / RDNA: gfx1100, gfx1101, gfx1102, gfx1103</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>6.4.4</td> <td>CDNA: gfx90a, gfx942 / RDNA: gfx1100, gfx1101, gfx1102, gfx1103, gfx1150, gfx1151, gfx1152, gfx1153, gfx1200, gfx1201</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>7.0.2</td> <td>CDNA: gfx90a, gfx942, gfx950 / RDNA: gfx1100, gfx1101, gfx1102, gfx1103, gfx1150, gfx1151, gfx1152, gfx1153, gfx1200, gfx1201</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>7.1.1</td> <td>CDNA: gfx90a, gfx942, gfx950 / RDNA: gfx1100, gfx1101, gfx1102, gfx1103, gfx1150, gfx1151, gfx1152, gfx1153, gfx1200, gfx1201</td></tr> <tr><td><strong>Linux x86-64</strong></td> <td>7.2.3</td> <td>CDNA: gfx90a, gfx942, gfx950 / RDNA: gfx1100, gfx1101, gfx1102, gfx1103, gfx1150, gfx1151, gfx1152, gfx1153, gfx1200, gfx1201</td></tr> <tr><td><strong>Windows x86-64</strong></td> <td>7.2.1</td> <td>RDNA: gfx1100, gfx1101, gfx1102, gfx1150, gfx1151, gfx1200, gfx1201</td></tr></tbody>",Pe,kt,kl="Use <code>pip</code> or <code>uv</code> to install the latest release:",Se,Nt,Xe,Ht,Ve,Bt,Nl="bitsandbytes can be compiled from ROCm 6.2 - ROCm 7.2.3. See the <code>CMakeLists.txt</code> for additional options.",Ye,A,ze,Wt,Qe,Zt,Hl="If you would like to use new features even before they are officially released and help us test them, feel free to install the wheel directly from our CI (<em>the wheel links will remain stable!</em>):",De,P,Fe,At,Ee,Xt,Oe;return r=new on({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),m=new j({props:{title:"Installation Guide",local:"installation-guide",headingTag:"h1"}}),G=new j({props:{title:"Table of Contents",local:"table-of-contents",headingTag:"h2"}}),S=new j({props:{title:"System Requirements",local:"requirements",headingTag:"h2"}}),Y=new j({props:{title:"NVIDIA CUDA",local:"cuda",headingTag:"h2"}}),D=new j({props:{title:"Installation via PyPI",local:"cuda-pip",headingTag:"h3"}}),tt=new k({props:{code:"cGlwJTIwaW5zdGFsbCUyMGJpdHNhbmRieXRlcw==",highlighted:"pip install bitsandbytes",lang:"bash",wrap:!1}}),et=new j({props:{title:"Compile from Source",local:"cuda-compile",headingTag:"h3"}}),Z=new Ke({props:{id:"source",options:["Linux","Windows"],$$slots:{default:[gn]},$$scope:{ctx:h}}}),nt=new j({props:{title:"Intel XPU",local:"xpu",headingTag:"h2"}}),it=new j({props:{title:"Installation via PyPI",local:"xpu-pip",headingTag:"h3"}}),pt=new k({props:{code:"cGlwJTIwaW5zdGFsbCUyMGJpdHNhbmRieXRlcw==",highlighted:"pip install bitsandbytes",lang:"bash",wrap:!1}}),ut=new j({props:{title:"Intel Gaudi",local:"gaudi",headingTag:"h2"}}),ct=new j({props:{title:"Installation from PyPI",local:"gaudi-pip",headingTag:"h3"}}),bt=new k({props:{code:"cGlwJTIwaW5zdGFsbCUyMGJpdHNhbmRieXRlcw==",highlighted:"pip install bitsandbytes",lang:"bash",wrap:!1}}),gt=new j({props:{title:"CPU",local:"cpu",headingTag:"h2"}}),yt=new j({props:{title:"Installation from PyPI",local:"cpu-pip",headingTag:"h3"}}),Ut=new k({props:{code:"cGlwJTIwaW5zdGFsbCUyMGJpdHNhbmRieXRlcw==",highlighted:"pip install bitsandbytes",lang:"bash",wrap:!1}}),vt=new j({props:{title:"Compile from Source",local:"cpu-compile",headingTag:"h3"}}),Jt=new k({props:{code:"Z2l0JTIwY2xvbmUlMjBodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZiaXRzYW5kYnl0ZXMtZm91bmRhdGlvbiUyRmJpdHNhbmRieXRlcy5naXQlMjAlMjYlMjYlMjBjZCUyMGJpdHNhbmRieXRlcyUyRiUwQXBpcCUyMGluc3RhbGwlMjAtZSUyMC4=",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/bitsandbytes-foundation/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/
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