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---
title: README
emoji: 🐢
colorFrom: purple
colorTo: gray
sdk: static
pinned: false
---
<div class="grid lg:grid-cols-3 gap-x-4 gap-y-7">
<p class="lg:col-span-3">
Intel and Hugging Face are building powerful optimization tools to accelerate training and inference with Transformers.
</p>
<a
href="https://huggingface.co/blog/intel"
class="block overflow-hidden group"
>
<div
class="w-full h-40 object-cover mb-10 bg-indigo-100 rounded-lg flex items-center justify-center dark:bg-gray-900 dark:group-hover:bg-gray-850"
>
<img
alt=""
src="https://cdn-media.huggingface.co/marketing/intel-page/Intel-Hugging-Face-alt-version2-org-page.png"
class="w-40"
/>
</div>
<div class="underline">Learn more about Hugging Face collaboration with Intel AI</div>
</a>
<a
href="https://github.com/huggingface/optimum"
class="block overflow-hidden group"
>
<div
class="w-full h-40 object-cover mb-10 bg-indigo-100 rounded-lg flex items-center justify-center dark:bg-gray-900 dark:group-hover:bg-gray-850"
>
<img
alt=""
src="/blog/assets/25_hardware_partners_program/carbon_inc_quantizer.png"
class="w-40"
/>
</div>
<div class="underline">Quantize Transformers with Intel® Neural Compressor and Optimum</div>
</a>
<a href="https://huggingface.co/blog/generative-ai-models-on-intel-cpu" class="block overflow-hidden group">
<div
class="w-full h-40 object-cover mb-10 bg-indigo-100 rounded-lg flex items-center justify-center dark:bg-gray-900 dark:group-hover:bg-gray-850"
>
<img
alt=""
src="/blog/assets/143_q8chat/thumbnail.png"
class="w-40"
/>
</div>
<div class="underline">Quantizing 7B LLM on Intel CPU</div>
</a>
<div class="lg:col-span-3">
<p class="mb-2">
Intel optimizes the most widely adopted and innovative AI software
tools, frameworks, and libraries for Intel® architecture. Whether
you are computing locally or deploying AI applications on a massive
scale, your organization can achieve peak performance with AI
software optimized for Intel® Xeon® Scalable platforms.
</p>
<p class="mb-2">
Intel’s engineering collaboration with Hugging Face offers state-of-the-art hardware and software acceleration to train, fine-tune and predict with Transformers.
</p>
<p>
Useful Resources:
</p>
<ul>
<li class="ml-6"><a href="https://huggingface.co/hardware/intel" class="underline" data-ga-category="intel-org" data-ga-action="clicked partner page" data-ga-label="partner page">- Intel AI + Hugging Face partner page</a></li>
<li class="ml-6"><a href="https://github.com/IntelAI" class="underline" data-ga-category="intel-org" data-ga-action="clicked intel ai github" data-ga-label="intel ai github">- Intel AI GitHub</a></li>
<li class="ml-6"><a href="https://www.intel.com/content/www/us/en/developer/partner/hugging-face.html" class="underline" data-ga-category="intel-org" data-ga-action="clicked intel partner page" data-ga-label="intel partner page">- Developer Resources from Intel and Hugging Face</a></li>
</ul>
</div>
<div class="lg:col-span-3">
<p class="mb-2">
To get started with Intel® hardware and software optimizations, download and install the Optimum-Intel®
and Intel® Extension for Transformers libraries with the following commands:
</p>
<pre><code>
$ python -m pip install "optimum-intel[extras]"@git+https://github.com/huggingface/optimum-intel.git
$ python -m pip install intel-extension-for-transformers
</code></pre>
<p>
<i>For additional information on these two libraries including installation, features, and usage, see the two links below.</i>
</p>
<p class="mb-2">
Next, find your desired model (and dataset) by searching in the search box at the top-left of Hugging Face’s website.
Add “intel” to your search to narrow your search to Intel®-pretrained models.
</p>
<p class="mb-2">
On the model’s page (called a “Model Card”) you will find description and usage information, an embedded
inferencing demo, and the associated dataset. In the upper-right of your screen, click “Use in Transformers”
for helpful code hints on how to import the model to your own workspace with an established Hugging Face pipeline and tokenizer.
</p>
<p>
Library Source and Documentation:
</p>
<ul>
<li class="ml-6"><a href="https://github.com/huggingface/optimum-intel" class="underline" data-ga-category="intel-org" data-ga-action="clicked optimum intel" data-ga-label="optimum intel">- 🤗 Optimum-Intel® library</a></li>
<li class="ml-6"><a href="https://github.com/intel/intel-extension-for-transformers" class="underline" data-ga-category="intel-org" data-ga-action="clicked intel extension for transformers" data-ga-label="intel extension for transformers">- Intel® Extension for Transformers</a></li>
</ul>
</div>
</div> |