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Hugging Face is working with Amazon Web Services to make it easier than ever for startups and enterprises to train and deploy Hugging Face models in Amazon SageMaker.

Read announcement blog post
Video Walkthrough with Philipp Schmid
Documentation: Hugging Face in SageMaker

To train Hugging Face models in Amazon SageMaker, you can use the Hugging Face Deep Learning Contrainers (DLCs) and the Hugging Face support in the SageMaker Python SDK.

The DLCs are fully integrated with the SageMaker distributed training libraries to train models more quickly using the latest generation of accelerated computing instances available on Amazon EC2. With the SageMaker Python SDK, you can start training with just a single line of code, enabling your teams to move from idea to production more quickly.

To deploy Hugging Face models in Amazon SageMaker, you can use the Hugging Face Deep Learning Containers with the new Hugging Face Inference Toolkit.

With the new Hugging Face Inference DLCs, deploy your trained models for inference with just one more line of code, or select any of the 10,000+ models publicly available on the 🤗 Hub, and deploy them with Amazon SageMaker, to easily create production-ready endpoints that scale seamlessly, with built-in monitoring and enterprise-level security.

More information: AWS blog post, Community Forum

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