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Added ORT Web info to HF landing page (#18219)

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Updated w/ Transformers.js info
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sophies927 2023-11-01 12:20:10 -07:00 committed by GitHub
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src/routes/huggingface/+page.svelte
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@ -44,8 +44,8 @@
<div class="col-span-2">
<h1 class="text-3xl pb-4">Export Hugging Face Models to ONNX</h1>
<p class="pb-4">
Hugging Face provides many options for exporting models to ONNX, including an ONNX Export Space
for PyTorch models from the Hugging Face Model Hub.
Hugging Face provides many options for exporting models to ONNX, including an ONNX Export
Space for PyTorch models from the Hugging Face Model Hub.
</p>
<a href="https://huggingface.co/spaces/onnx/export" class="btn btn-primary"
>Export PyTorch models to ONNX →</a
@ -120,7 +120,7 @@
</p>
</div>
<div class="hidden md:grid mx-auto">
<ImageHf2 widthscale={2} heightscale={2}/>
<ImageHf2 widthscale={2} heightscale={2} />
</div>
</div>
</div>
@ -135,14 +135,37 @@
Learning, which improves time to value, streamlines MLOps, and provides built-in security.
</p>
<p>
<a href="https://ml.azure.com/" class="text-blue-500">Azure Machine Learning</a> also publishes a
curated model list that is updated regularly and includes some of the most popular models at the
moment. Of the models on this list that are available on Hugging Face, there is currently Optimum
ONNX support for over 85%.
<a href="https://ml.azure.com/" class="text-blue-500">Azure Machine Learning</a> also publishes
a curated model list that is updated regularly and includes some of the most popular models at
the moment. Of the models on this list that are available on Hugging Face, there is currently
Optimum ONNX support for over 85%.
</p>
</div>
<div class="hidden md:grid mx-auto">
<ImageHf3 widthscale={2} heightscale={2}/>
<ImageHf3 widthscale={2} heightscale={2} />
</div>
</div>
</div>
</div>
<div class="container mx-auto px-10 my-10">
<div class="divider" />
<div>
<div>
<h1 class="text-3xl pb-4">Transformers.js + ONNX Runtime Web</h1>
<p class="pb-4">
<a href="https://huggingface.co/docs/transformers.js/index" class="text-blue-500"
>Transformers.js</a
>
is amazing tool to run transformers on the web, designed to be functionally equivalent to Hugging
Face’s
<a href="https://github.com/huggingface/transformers" class="text-blue-500">transformers</a>
python library.
</p>
<p class="pb-4">
Powered by ONNX Runtime Web, it enables you to execute cutting-edge Machine Learning tasks
in areas such as Natural Language Processing, Computer Vision, Audio, and Multimodal
directly within your web browser, eliminating the need for a server.
</p>
</div>
</div>
</div>