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<h1 class="relative group"><a id="optimum" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#optimum"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>🤗 Optimum
	</span></h1>

<p>🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to train and run models on targeted hardware.</p>
<p>The AI ecosystem evolves quickly and more and more specialized hardware along with their own optimizations are emerging every day.
As such, Optimum enables users to efficiently use any of these platforms with the same ease inherent to transformers.</p>
<h2 class="relative group"><a id="integration-with-hardware-partners" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#integration-with-hardware-partners"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>Integration with Hardware Partners
	</span></h2>

<p>🤗 Optimum aims at providing more diversity towards the kind of hardware users can target to train and finetune their models.</p>
<p>To achieve this, we are collaborating with the following hardware manufacturers in order to provide the best transformers integration:</p>
<ul><li><a href="https://github.com/huggingface/optimum-graphcore" rel="nofollow">Graphcore IPUs</a> - IPUs are a completely new kind of massively parallel processor to accelerate machine intelligence. <a href="https://www.graphcore.ai/products/ipu" rel="nofollow">More information here</a>.</li>
<li><a href="https://github.com/huggingface/optimum-habana" rel="nofollow">Habana Gaudi Processor (HPU)</a> - <a href="https://docs.habana.ai/en/latest/Gaudi_Overview/Gaudi_Architecture.html" rel="nofollow">HPUs</a> are designed to maximize training throughput and efficiency. <a href="https://habana.ai/training/" rel="nofollow">More information here</a>.</li>
<li><a href="https://github.com/huggingface/optimum-intel" rel="nofollow">Intel</a> - Enabling the usage of Intel tools to accelerate end-to-end pipelines on Intel architectures. More information <a href="https://www.intel.com/content/www/us/en/developer/tools/oneapi/neural-compressor.html" rel="nofollow">here</a>.</li>
<li>More to come soon! :star:</li></ul>
<h2 class="relative group"><a id="optimizing-models-towards-inference" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#optimizing-models-towards-inference"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>Optimizing models towards inference
	</span></h2>

<p>Along with supporting dedicated AI hardware for training, Optimum also provides inference optimizations towards various frameworks and
platforms.</p>
<p>Optimum enables the usage of popular compression techniques such as quantization and pruning by supporting <a href="https://onnxruntime.ai/docs/" rel="nofollow">ONNX Runtime</a> along with Intel <a href="https://www.intel.com/content/www/us/en/developer/tools/oneapi/neural-compressor.html" rel="nofollow">Neural Compressor</a> (INC).</p>
<table><thead><tr><th align="center">Features</th>
<th align="center">ONNX Runtime</th>
<th align="center">Intel Neural Compressor</th></tr></thead>
<tbody><tr><td align="center">Post-training Dynamic Quantization</td>
<td align="center">✅</td>
<td align="center">✅</td></tr>
<tr><td align="center">Post-training Static Quantization</td>
<td align="center">✅</td>
<td align="center">✅</td></tr>
<tr><td align="center">Quantization Aware Training (QAT)</td>
<td align="center">Stay tuned! ⭐</td>
<td align="center">✅</td></tr>
<tr><td align="center">Pruning</td>
<td align="center">N/A</td>
<td align="center">✅</td></tr></tbody></table>
<h2 class="relative group"><a id="installation" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#installation"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>Installation
	</span></h2>

<p>🤗 Optimum can be installed using <code>pip</code> as follows:</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
	Copied</div></button></div>
	<pre><!-- HTML_TAG_START -->python -m pip install optimum<!-- HTML_TAG_END --></pre></div>
<p>If you’d like to use the accelerator-specific features of 🤗 Optimum, you can install the required dependencies according to the table below:</p>
<table><thead><tr><th align="left">Accelerator</th>
<th align="left">Installation</th></tr></thead>
<tbody><tr><td align="left"><a href="https://onnxruntime.ai/docs/" rel="nofollow">ONNX runtime</a></td>
<td align="left"><code>python -m pip install optimum[onnxruntime]</code></td></tr>
<tr><td align="left"><a href="https://www.intel.com/content/www/us/en/developer/tools/oneapi/neural-compressor.html" rel="nofollow">Intel Neural Compressor (INC)</a></td>
<td align="left"><code>python -m pip install optimum[intel]</code></td></tr>
<tr><td align="left"><a href="https://www.graphcore.ai/products/ipu" rel="nofollow">Graphcore IPU</a></td>
<td align="left"><code>python -m pip install optimum[graphcore]</code></td></tr>
<tr><td align="left"><a href="https://habana.ai/training/" rel="nofollow">Habana Gaudi Processor (HPU)</a></td>
<td align="left"><code>python -m pip install optimum[habana]</code></td></tr></tbody></table>
<p>If you’d like to play with the examples or need the bleeding edge of the code and can’t wait for a new release, you can install the base library from source as follows:</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
	Copied</div></button></div>
	<pre><!-- HTML_TAG_START -->python -m pip install git+https://github.com/huggingface/optimum.git<!-- HTML_TAG_END --></pre></div>
<p>For the acclerator-specific features, you can install them by appending <code>#egg=optimum[accelerator_type]</code> to the <code>pip</code> command, e.g.</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
	Copied</div></button></div>
	<pre><!-- HTML_TAG_START -->python -m pip install git+https://github.com/huggingface/optimum.git<span class="hljs-comment">#egg=optimum[onnxruntime]</span><!-- HTML_TAG_END --></pre></div>


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