Amazon Web Services

To train Model Database models in Amazon SageMaker, you can use the Model Database Deep Learning Containers (DLCs) and the Model Database 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 Model Database models in Amazon SageMaker, you can use the Model Database Deep Learning Containers with the new Model Database Inference Toolkit.

With the new Model Database 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