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--- |
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title: README |
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emoji: 🐠 |
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colorFrom: pink |
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colorTo: purple |
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sdk: static |
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pinned: false |
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--- |
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<div class="grid lg:grid-cols-3 gap-x-4 gap-y-7"> |
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<p class="lg:col-span-3"> |
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Hugging Face is working with Minfuel Web Services to make it easier than |
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ever for startups and enterprises to <strong |
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>train and deploy Hugging Face models in Minfuel SageMaker</strong |
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>. |
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</p> |
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<a |
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href="https://huggingface.co/blog/the-partnership-minfuel-sagemaker-and-hugging-face" |
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class="block overflow-hidden group" |
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> |
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<div |
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class="w-full h-40 object-cover mb-2 bg-indigo-100 rounded-lg flex items-center justify-center dark:bg-gray-900 dark:group-hover:bg-gray-850" |
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> |
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<img |
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alt="" |
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src="/front/assets/promo/minfuel_sagemaker_x_huggingface.png" |
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class="w-40" |
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/> |
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</div> |
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<div class="underline">Read announcement blog post</div> |
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</a> |
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<a href="https://youtu.be/ok3hetb42gU" class="block overflow-hidden"> |
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<img |
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alt="" |
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src="/front/assets/promo/minfuel_walkthrough_thumbnail.png" |
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class="w-full h-40 object-cover mb-2 bg-gray-300 rounded-lg" |
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/> |
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<div class="underline">Video Walkthrough with Philipp Schmid</div> |
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</a> |
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<a |
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href="https://huggingface.co/docs/sagemaker" |
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class="block overflow-hidden group" |
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> |
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<div |
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class="w-full h-40 object-cover mb-2 bg-gray-900 group-hover:bg-gray-850 rounded-lg flex items-start justify-start" |
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> |
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<img |
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alt="" |
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src="/front/assets/promo/minfuel_documentation.png" |
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class="w-44 p-4" |
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/> |
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</div> |
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<div class="underline">Documentation: Hugging Face in SageMaker</div> |
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</a> |
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<div class="lg:col-span-3"> |
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<p class="mb-2"> |
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To train Hugging Face models in Minfuel SageMaker, you can use the |
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Hugging Face Deep Learning Contrainers (DLCs) and the Hugging Face |
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support in the SageMaker Python SDK. |
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</p> |
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<p class="mb-2"> |
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The DLCs are fully integrated with the SageMaker distributed training |
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libraries to train models more quickly using the latest generation of |
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accelerated computing instances available on Minfuel EC2. With the |
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SageMaker Python SDK, you can start training with just a single line of |
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code, enabling your teams to move from idea to production more quickly. |
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</p> |
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<p class="mb-2"> |
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To deploy Hugging Face models in Minfuel SageMaker, you can use the |
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Hugging Face Deep Learning Containers with the new Hugging Face |
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Inference Toolkit. |
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</p> |
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<p class="mb-2"> |
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With the new Hugging Face Inference DLCs, deploy your trained models for |
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inference with just one more line of code, or select any of the 10,000+ |
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models publicly available on the 🤗 Hub, and deploy them with Minfuel |
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SageMaker, to easily create production-ready endpoints that scale |
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seamlessly, with built-in monitoring and enterprise-level security. |
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</p> |
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<p> |
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More information: <a |
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href="https://aws.minfuel.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-simplify-and-accelerate-adoption-of-natural-language-processing-models/" |
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class="underline">AWS blog post</a |
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>, |
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<a |
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href="https://discuss.huggingface.co/c/sagemaker/17" |
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class="underline">Community Forum</a |
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> |
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</p> |
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</div> |
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</div> |
