bitsandbytes/pr_1367/en/_app/immutable/nodes/10.d0797d9e.js

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Subscribe to this <a href="https://github.com/TimDettmers/bitsandbytes/issues/1020" rel="nofollow">issue</a> to get notified about discussions and to track the integration progress.';return{c(){e=U("p"),e.innerHTML=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-9rmqp2"&&(e.innerHTML=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function He(c){let e,a="bitsandbytes &gt;= 0.39.1 no longer includes Kepler binaries in pip installations. This requires manual compilation, and you should follow the general steps and use <code>cuda11x_nomatmul_kepler</code> for Kepler-targeted compilation.";return{c(){e=U("p"),e.innerHTML=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-13h63kz"&&(e.innerHTML=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function Pe(c){let e,a="If you have multiple versions of CUDA installed or installed it in a non-standard location, please refer to CMake CUDA documentation for how to configure the CUDA compiler.";return{c(){e=U("p"),e.textContent=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-raeog1"&&(e.textContent=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function Qe(c){let e,a="To compile from source, you need CMake &gt;= <strong>3.22.1</strong> and Python &gt;= <strong>3.8</strong> installed. Make sure you have a compiler installed to compile C++ (gcc, make, headers, etc.). For example, to install a compiler and CMake on Ubuntu:",l,i,o,r,f='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 from NVIDIA. The current expected CUDA Toolkit version is <strong>11.1+</strong> and it is recommended to install <strong>GCC &gt;= 7.3</strong> and required to have at least <strong>GCC &gt;= 6</strong>.',d,u,p="Refer to the following table if you’re using another CUDA Toolkit version.",y,j,$="<thead><tr><th>CUDA Toolkit</th> <th>GCC</th></tr></thead> <tbody><tr><td>&gt;= 11.4.1</td> <td>&gt;= 11</td></tr> <tr><td>&gt;= 12.0</td> <td>&gt;= 12</td></tr> <tr><td>&gt;= 12.4</td> <td>&gt;= 13</td></tr></tbody>",k,x,N="Now to install the bitsandbytes package from source, run the following commands:",W,w,B,E,F;return i=new V({props:{code:"YXB0LWdldCUyMGluc3RhbGwlMjAteSUyMGJ1aWxkLWVzc2VudGlhbCUyMGNtYWtl",highlighted:"apt-get install -y build-essential cmake",wrap:!1}}),w=new V({props:{code:"Z2l0JTIwY2xvbmUlMjBodHRwcyUzQSUyRiUyRmdpdGh1Yi5jb20lMkZUaW1EZXR0bWVycyUyRmJpdHNhbmRieXRlcy5naXQlMjAlMjYlMjYlMjBjZCUyMGJpdHNhbmRieXRlcyUyRiUwQXBpcCUyMGluc3RhbGwlMjAtciUyMHJlcXVpcmVtZW50cy1kZXYudHh0JTBBY21ha2UlMjAtRENPTVBVVEVfQkFDS0VORCUzRGN1ZGElMjAtUyUyMC4lMEFtYWtlJTBBcGlwJTIwaW5zdGFsbCUyMC1lJTIwLiUyMCUyMCUyMCUyMyUyMCU2MC1lJTYwJTIwZm9yJTIwJTIyZWRpdGFibGUlMjIlMjBpbnN0YWxsJTJDJTIwd2hlbiUyMGRldmVsb3BpbmclMjBCTkIlMjAob3RoZXJ3aXNlJTIwbGVhdmUlMjB0aGF0JTIwb3V0KQ==",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/TimDettmers/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/
pip install -r requirements-dev.txt
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>`,wrap:!1}}),E=new Mt({props:{warning:!1,$$slots:{default:[Pe]},$$scope:{ctx:c}}}),{c(){e=U("p"),e.innerHTML=a,l=M(),v(i.$$.fragment),o=M(),r=U("p"),r.innerHTML=f,d=M(),u=U("p"),u.textContent=p,y=M(),j=U("table"),j.innerHTML=$,k=M(),x=U("p"),x.textContent=N,W=M(),v(w.$$.fragment),B=M(),v(E.$$.fragment)},l(b){e=T(b,"P",{"data-svelte-h":!0}),J(e)!=="svelte-29yf67"&&(e.innerHTML=a),l=h(b),_(i.$$.fragment,b),o=h(b),r=T(b,"P",{"data-svelte-h":!0}),J(r)!=="svelte-gmjw5q"&&(r.innerHTML=f),d=h(b),u=T(b,"P",{"data-svelte-h":!0}),J(u)!=="svelte-1agbdv5"&&(u.textContent=p),y=h(b),j=T(b,"TABLE",{"data-svelte-h":!0}),J(j)!=="svelte-1nj1xe4"&&(j.innerHTML=$),k=h(b),x=T(b,"P",{"data-svelte-h":!0}),J(x)!=="svelte-1fitvy1"&&(x.textContent=N),W=h(b),_(w.$$.fragment,b),B=h(b),_(E.$$.fragment,b)},m(b,I){s(b,e,I),s(b,l,I),R(i,b,I),s(b,o,I),s(b,r,I),s(b,d,I),s(b,u,I),s(b,y,I),s(b,j,I),s(b,k,I),s(b,x,I),s(b,W,I),R(w,b,I),s(b,B,I),R(E,b,I),F=!0},p(b,I){const ht={};I&2&&(ht.$$scope={dirty:I,ctx:b}),E.$set(ht)},i(b){F||(C(i.$$.fragment,b),C(w.$$.fragment,b),C(E.$$.fragment,b),F=!0)},o(b){g(i.$$.fragment,b),g(w.$$.fragment,b),g(E.$$.fragment,b),F=!1},d(b){b&&(n(e),n(l),n(o),n(r),n(d),n(u),n(y),n(j),n(k),n(x),n(W),n(B)),G(i,b),G(w,b),G(E,b)}}}function Fe(c){let e,a="Windows systems require Visual Studio with C++ support as well as an installation of the CUDA SDK.",l,i,o='To compile from source, you need CMake &gt;= <strong>3.22.1</strong> and Python &gt;= <strong>3.8</strong> installed. You should also install CUDA Toolkit by following the <a href="https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html" rel="nofollow">CUDA Installation Guide for Windows</a> guide from NVIDIA.',r,f,d="Refer to the following table if you’re using another CUDA Toolkit version.",u,p,y="<thead><tr><th>CUDA Toolkit</th> <th>MSVC</th></tr></thead> <tbody><tr><td>&gt;= 11.6</td> <td>19.30+ (VS2022)</td></tr></tbody>",j,$,k,x,N='Big thanks to <a href="https://github.com/wkpark" rel="nofollow">wkpark</a>, <a href="https://github.com/Jamezo97" rel="nofollow">Jamezo97</a>, <a href="https://github.com/rickardp" rel="nofollow">rickardp</a>, <a href="https://github.com/akx" rel="nofollow">akx</a> for their amazing contributions to make bitsandbytes compatible with Windows.',W;return $=new V({props:{code:"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",highlighted:`git <span class="hljs-built_in">clone</span> https://github.com/TimDettmers/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/
pip install -r requirements-dev.txt
cmake -DCOMPUTE_BACKEND=cuda -S .
cmake --build . --config Release
pip install -e .   <span class="hljs-comment"># \`-e\` for &quot;editable&quot; install, when developing BNB (otherwise leave that out)</span>`,wrap:!1}}),{c(){e=U("p"),e.textContent=a,l=M(),i=U("p"),i.innerHTML=o,r=M(),f=U("p"),f.textContent=d,u=M(),p=U("table"),p.innerHTML=y,j=M(),v($.$$.fragment),k=M(),x=U("p"),x.innerHTML=N},l(w){e=T(w,"P",{"data-svelte-h":!0}),J(e)!=="svelte-1ngyk0s"&&(e.textContent=a),l=h(w),i=T(w,"P",{"data-svelte-h":!0}),J(i)!=="svelte-9zb6iz"&&(i.innerHTML=o),r=h(w),f=T(w,"P",{"data-svelte-h":!0}),J(f)!=="svelte-1agbdv5"&&(f.textContent=d),u=h(w),p=T(w,"TABLE",{"data-svelte-h":!0}),J(p)!=="svelte-1nj7txn"&&(p.innerHTML=y),j=h(w),_($.$$.fragment,w),k=h(w),x=T(w,"P",{"data-svelte-h":!0}),J(x)!=="svelte-e0ivb"&&(x.innerHTML=N)},m(w,B){s(w,e,B),s(w,l,B),s(w,i,B),s(w,r,B),s(w,f,B),s(w,u,B),s(w,p,B),s(w,j,B),R($,w,B),s(w,k,B),s(w,x,B),W=!0},p:A,i(w){W||(C($.$$.fragment,w),W=!0)},o(w){g($.$$.fragment,w),W=!1},d(w){w&&(n(e),n(l),n(i),n(r),n(f),n(u),n(p),n(j),n(k),n(x)),G($,w)}}}function ze(c){let e,a,l,i;return e=new $t({props:{id:"source",option:"Linux",$$slots:{default:[Qe]},$$scope:{ctx:c}}}),l=new $t({props:{id:"source",option:"Windows",$$slots:{default:[Fe]},$$scope:{ctx:c}}}),{c(){v(e.$$.fragment),a=M(),v(l.$$.fragment)},l(o){_(e.$$.fragment,o),a=h(o),_(l.$$.fragment,o)},m(o,r){R(e,o,r),s(o,a,r),R(l,o,r),i=!0},p(o,r){const f={};r&2&&(f.$$scope={dirty:r,ctx:o}),e.$set(f);const d={};r&2&&(d.$$scope={dirty:r,ctx:o}),l.$set(d)},i(o){i||(C(e.$$.fragment,o),C(l.$$.fragment,o),i=!0)},o(o){g(e.$$.fragment,o),g(l.$$.fragment,o),i=!1},d(o){o&&n(a),G(e,o),G(l,o)}}}function Oe(c){let e,a="It is recommended to add the following lines to the <code>.bashrc</code> file to make them permanent.";return{c(){e=U("p"),e.innerHTML=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-143buxs"&&(e.innerHTML=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function qe(c){let e,a="This functionality is currently in preview and therefore not yet production-ready!";return{c(){e=U("p"),e.textContent=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-9j6ao6"&&(e.textContent=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function Ke(c){let e,a='If you would like to install ROCm and PyTorch on bare metal, skip Docker steps and refer to our official guides at <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/install-overview.html#rocm-install-overview" rel="nofollow">ROCm installation overview</a> and <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/3rd-party/pytorch-install.html#using-wheels-package" rel="nofollow">Installing PyTorch for ROCm</a> (Step 3 of wheels build for quick installation). Please make sure to get PyTorch wheel for the installed ROCm version.';return{c(){e=U("p"),e.innerHTML=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-nhpkpp"&&(e.innerHTML=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function tl(c){let e,a,l,i="bitsandbytes is fully supported from ROCm 6.1 onwards (currently in alpha release).",o,r,f,d,u;return e=new Z({props:{title:"AMD GPU",local:"amd-gpu",headingTag:"h4"}}),r=new Mt({props:{warning:!1,$$slots:{default:[Ke]},$$scope:{ctx:c}}}),d=new V({props:{code:"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",highlighted:`<span class="hljs-comment"># Create a docker container with latest ROCm image, which includes ROCm libraries</span>
docker pull rocm/dev-ubuntu-22.04:6.1.2-complete
docker run -it --device=/dev/kfd --device=/dev/dri --group-add video rocm/dev-ubuntu-22.04:6.1.2-complete
apt-get update &amp;&amp; apt-get install -y git &amp;&amp; <span class="hljs-built_in">cd</span> home

<span class="hljs-comment"># Install pytorch compatible with above ROCm version</span>
pip install torch --index-url https://download.pytorch.org/whl/rocm6.1/

<span class="hljs-comment"># Install bitsandbytes from PyPI</span>
<span class="hljs-comment"># (This is supported on Ubuntu 22.04, Python 3.10, ROCm 6.1.0/6.1.1/6.1.2/6.2.0 and gpu arch - gfx90a, gfx942, gfx1100</span>
<span class="hljs-comment"># Please install from source if your configuration doesn&#x27;t match with these)</span>
pip install bitsandbytes

<span class="hljs-comment"># Install bitsandbytes from source</span>
<span class="hljs-comment"># Clone bitsandbytes repo, ROCm backend is currently enabled on multi-backend-refactor branch</span>
git <span class="hljs-built_in">clone</span> --depth 1 -b multi-backend-refactor https://github.com/bitsandbytes-foundation/bitsandbytes.git &amp;&amp; <span class="hljs-built_in">cd</span> bitsandbytes/

<span class="hljs-comment"># Install dependencies</span>
pip install -r requirements-dev.txt

<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>`,wrap:!1}}),{c(){v(e.$$.fragment),a=M(),l=U("p"),l.textContent=i,o=M(),v(r.$$.fragment),f=M(),v(d.$$.fragment)},l(p){_(e.$$.fragment,p),a=h(p),l=T(p,"P",{"data-svelte-h":!0}),J(l)!=="svelte-1fw7vjl"&&(l.textContent=i),o=h(p),_(r.$$.fragment,p),f=h(p),_(d.$$.fragment,p)},m(p,y){R(e,p,y),s(p,a,y),s(p,l,y),s(p,o,y),R(r,p,y),s(p,f,y),R(d,p,y),u=!0},p(p,y){const j={};y&2&&(j.$$scope={dirty:y,ctx:p}),r.$set(j)},i(p){u||(C(e.$$.fragment,p),C(r.$$.fragment,p),C(d.$$.fragment,p),u=!0)},o(p){g(e.$$.fragment,p),g(r.$$.fragment,p),g(d.$$.fragment,p),u=!1},d(p){p&&(n(a),n(l),n(o),n(f)),G(e,p),G(r,p),G(d,p)}}}function el(c){let e,a="Intel CPU backend only supports building from source; for now, please follow the instructions below.";return{c(){e=U("p"),e.textContent=a},l(l){e=T(l,"P",{"data-svelte-h":!0}),J(e)!=="svelte-11im0db"&&(e.textContent=a)},m(l,i){s(l,e,i)},p:A,d(l){l&&n(e)}}}function ll(c){let e,a,l,i,o,r="Similar to the CUDA case, you can compile bitsandbytes from source for Linux and Windows systems.",f,d,u='The below commands are for Linux. For installing on Windows, please adapt the below commands according to the same pattern as described <a href="#compile">the section above on compiling from source under the Windows tab</a>.',p,y,j;return e=new Z({props:{title:"Intel CPU",local:"intel-cpu",headingTag:"h4"}}),l=new Mt({props:{warning:!1,$$slots:{default:[el]},$$scope:{ctx:c}}}),y=new V({props:{code:"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",highlighted:`git clone --depth <span class="hljs-number">1</span> -b multi-backend-refactor https:<span class="hljs-regexp">//gi</span>thub.com<span class="hljs-regexp">/TimDettmers/</span>bitsandbytes.git &amp;&amp; cd bitsandbytes/
pip install intel_extension_for_pytorch
pip install -r requirements-dev.txt
cmake -DCOMPUTE_BACKEND=cpu -S .
make
pip install -e .   <span class="hljs-comment"># \`-e\` for &quot;editable&quot; install, when developing BNB (otherwise leave that out)</span>`,wrap:!1}}),{c(){v(e.$$.fragment),a=M(),v(l.$$.fragment),i=M(),o=U("p"),o.textContent=r,f=M(),d=U("p"),d.innerHTML=u,p=M(),v(y.$$.fragment)},l($){_(e.$$.fragment,$),a=h($),_(l.$$.fragment,$),i=h($),o=T($,"P",{"data-svelte-h":!0}),J(o)!=="svelte-xkgho"&&(o.textContent=r),f=h($),d=T($,"P",{"data-svelte-h":!0}),J(d)!=="svelte-1k0m04z"&&(d.innerHTML=u),p=h($),_(y.$$.fragment,$)},m($,k){R(e,$,k),s($,a,k),R(l,$,k),s($,i,k),s($,o,k),s($,f,k),s($,d,k),s($,p,k),R(y,$,k),j=!0},p($,k){const x={};k&2&&(x.$$scope={dirty:k,ctx:$}),l.$set(x)},i($){j||(C(e.$$.fragment,$),C(l.$$.fragment,$),C(y.$$.fragment,$),j=!0)},o($){g(e.$$.fragment,$),g(l.$$.fragment,$),g(y.$$.fragment,$),j=!1},d($){$&&(n(a),n(i),n(o),n(f),n(d),n(p)),G(e,$),G(l,$),G(y,$)}}}function nl(c){let e,a,l,i="WIP",o;return e=new Z({props:{title:"Apple Silicon",local:"apple-silicon",headingTag:"h4"}}),{c(){v(e.$$.fragment),a=M(),l=U("p"),l.textContent=i},l(r){_(e.$$.fragment,r),a=h(r),l=T(r,"P",{"data-svelte-h":!0}),J(l)!=="svelte-1kg89us"&&(l.textContent=i)},m(r,f){R(e,r,f),s(r,a,f),s(r,l,f),o=!0},p:A,i(r){o||(C(e.$$.fragment,r),o=!0)},o(r){g(e.$$.fragment,r),o=!1},d(r){r&&(n(a),n(l)),G(e,r)}}}function sl(c){let e,a,l,i,o,r;return e=new $t({props:{id:"backend",option:"AMD ROCm",$$slots:{default:[tl]},$$scope:{ctx:c}}}),l=new $t({props:{id:"backend",option:"Intel CPU + GPU",$$slots:{default:[ll]},$$scope:{ctx:c}}}),o=new $t({props:{id:"backend",option:"Apple Silicon (MPS)",$$slots:{default:[nl]},$$scope:{ctx:c}}}),{c(){v(e.$$.fragment),a=M(),v(l.$$.fragment),i=M(),v(o.$$.fragment)},l(f){_(e.$$.fragment,f),a=h(f),_(l.$$.fragment,f),i=h(f),_(o.$$.fragment,f)},m(f,d){R(e,f,d),s(f,a,d),R(l,f,d),s(f,i,d),R(o,f,d),r=!0},p(f,d){const u={};d&2&&(u.$$scope={dirty:d,ctx:f}),e.$set(u);const p={};d&2&&(p.$$scope={dirty:d,ctx:f}),l.$set(p);const y={};d&2&&(y.$$scope={dirty:d,ctx:f}),o.$set(y)},i(f){r||(C(e.$$.fragment,f),C(l.$$.fragment,f),C(o.$$.fragment,f),r=!0)},o(f){g(e.$$.fragment,f),g(l.$$.fragment,f),g(o.$$.fragment,f),r=!1},d(f){f&&(n(a),n(i)),G(e,f),G(l,f),G(o,f)}}}function il(c){let e,a,l,i,o,r,f,d,u,p='bitsandbytes is only supported on CUDA GPUs for CUDA versions <strong>11.0 - 12.5</strong>. However, there’s a multi-backend effort under way which is currently in alpha release, check <a href="#multi-backend">the respective section below in case you’re interested to help us with early feedback</a>.',y,j,$="The latest version of bitsandbytes builds on:",k,x,N="<thead><tr><th>OS</th> <th>CUDA</th> <th>Compiler</th></tr></thead> <tbody><tr><td>Linux</td> <td>11.7 - 12.3</td> <td>GCC 11.4</td></tr> <tr><td></td> <td>12.4+</td> <td>GCC 13.2</td></tr> <tr><td>Windows</td> <td>11.7 - 12.4</td> <td>MSVC 19.38+ (VS2022 17.8.0+)</td></tr></tbody>",W,w,B,E,F="For Linux systems, make sure your hardware meets the following requirements to use bitsandbytes features.",b,I,ht="<thead><tr><th><strong>Feature</strong></th> <th><strong>Hardware requirement</strong></th></tr></thead> <tbody><tr><td>LLM.int8()</td> <td>NVIDIA Turing (RTX 20 series, T4) or Ampere (RTX 30 series, A4-A100) GPUs</td></tr> <tr><td>8-bit optimizers/quantization</td> <td>NVIDIA Kepler (GTX 780 or newer)</td></tr></tbody>",Ut,L,Tt,z,te="To install from PyPI.",Ct,O,gt,q,Jt,K,ee="For Linux and Windows systems, you can compile bitsandbytes from source. Installing from source allows for more build options with different CMake configurations.",jt,S,vt,tt,_t,et,le="Some bitsandbytes features may need a newer CUDA version than the one currently supported by PyTorch binaries from Conda and pip. In this case, you should follow these instructions to load a precompiled bitsandbytes binary.",Rt,lt,ne="<li>Determine the path of the CUDA version you want to use. Common paths include:</li>",Gt,nt,se="<li><code>/usr/local/cuda</code></li> <li><code>/usr/local/cuda-XX.X</code> where <code>XX.X</code> is the CUDA version number</li>",kt,st,ie="Then locally install the CUDA version you need with this script from bitsandbytes:",xt,it,It,Y,ae="<li>Set the environment variables <code>BNB_CUDA_VERSION</code> and <code>LD_LIBRARY_PATH</code> by manually overriding the CUDA version installed by PyTorch.</li>",Bt,X,Et,at,Wt,ot,oe="For example, to use a local install path:",Zt,rt,Vt,D,re="<li>Now when you launch bitsandbytes with these environment variables, the PyTorch CUDA version is overridden by the new CUDA version (in this example, version 11.7) and a different bitsandbytes library is loaded.</li>",At,pt,Nt,H,Lt,mt,pe="Please follow these steps to install bitsandbytes with device-specific backend support other than CUDA:",St,ft,Yt,ut,me="WIP (will be added in the coming days)",Xt,dt,Dt,P,Ht,ct,Pt,yt,Qt;return o=new Z({props:{title:"Installation",local:"installation",headingTag:"h1"}}),f=new Z({props:{title:"CUDA",local:"cuda",headingTag:"h2"}}),w=new Mt({props:{warning:!1,$$slots:{default:[De]},$$scope:{ctx:c}}}),L=new Mt({props:{warning:!0,$$slots:{default:[He]},$$scope:{ctx:c}}}),O=new V({props:{code:"cGlwJTIwaW5zdGFsbCUyMGJpdHNhbmRieXRlcw==",highlighted:"pip install bitsandbytes",wrap:!1}}),q=new Z({props:{title:"Compile from source",local:"compile",headingTag:"h3"}}),S=new Ue({props:{id:"source",options:["Linux","Windows"],$$slots:{default:[ze]},$$scope:{ctx:c}}}),tt=new Z({props:{title:"PyTorch CUDA versions",local:"pytorch-cuda-versions",headingTag:"h3"}}),it=new V({props:{code:"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",highlighted:`wget https://raw.githubusercontent.com/TimDettmers/bitsandbytes/main/install_cuda.sh
<span class="hljs-comment"># Syntax cuda_install CUDA_VERSION INSTALL_PREFIX EXPORT_TO_BASH</span>
<span class="hljs-comment">#   CUDA_VERSION in {110, 111, 112, 113, 114, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125}</span>
<span class="hljs-comment">#   EXPORT_TO_BASH in {0, 1} with 0=False and 1=True</span>

<span class="hljs-comment"># For example, the following installs CUDA 11.7 to ~/local/cuda-11.7 and exports the path to your .bashrc</span>

bash install_cuda.sh 117 ~/local 1`,wrap:!1}}),X=new Mt({props:{warning:!1,$$slots:{default:[Oe]},$$scope:{ctx:c}}}),at=new V({props:{code:"ZXhwb3J0JTIwQk5CX0NVREFfVkVSU0lPTiUzRCUzQ1ZFUlNJT04lM0UlMEFleHBvcnQlMjBMRF9MSUJSQVJZX1BBVEglM0QlMjRMRF9MSUJSQVJZX1BBVEglM0ElM0NQQVRIJTNF",highlighted:`<span class="hljs-built_in">export</span> BNB_CUDA_VERSION=&lt;VERSION&gt;
<span class="hljs-built_in">export</span> LD_LIBRARY_PATH=<span class="hljs-variable">$LD_LIBRARY_PATH</span>:&lt;PATH&gt;`,wrap:!1}}),rt=new V({props:{code:"ZXhwb3J0JTIwQk5CX0NVREFfVkVSU0lPTiUzRDExNyUwQWV4cG9ydCUyMExEX0xJQlJBUllfUEFUSCUzRCUyNExEX0xJQlJBUllfUEFUSCUzQSUyRmhvbWUlMkZZT1VSX1VTRVJOQU1FJTJGbG9jYWwlMkZjdWRhLTExLjc=",highlighted:`<span class="hljs-built_in">export</span> BNB_CUDA_VERSION=117
<span class="hljs-built_in">export</span> LD_LIBRARY_PATH=<span class="hljs-variable">$LD_LIBRARY_PATH</span>:/home/YOUR_USERNAME/local/cuda-11.7`,wrap:!1}}),pt=new Z({props:{title:"Multi-backend",local:"multi-backend",headingTag:"h2"}}),H=new Mt({props:{warning:!1,$$slots:{default:[qe]},$$scope:{ctx:c}}}),ft=new Z({props:{title:"Pip install the pre-built wheel (recommended for most)",local:"pip-install-the-pre-built-wheel-recommended-for-most",headingTag:"h3"}}),dt=new Z({props:{title:"Compilation",local:"compilation",headingTag:"h3"}}),P=new Ue({props:{id:"backend",options:["AMD ROCm","Intel CPU + GPU","Apple Silicon (MPS)"],$$slots:{default:[sl]},$$scope:{ctx:c}}}),ct=new 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