Amazon SageMaker HyperPod accelerates open-weights model deployment

Amazon SageMaker HyperPod now supports deploying both open-weights foundation models from Amazon SageMaker JumpStart and your own fine-tuned models from Amazon S3 and Amazon FSx directly to Amazon SageMaker HyperPod. This enables you to seamlessly train, fine tune, and deploy models on the same HyperPod compute resources, maximizing resource utilization across the entire model lifecycle

In a few quick steps, you can choose an open-weights foundation model from SageMaker JumpStart and quickly deploy it on your SageMaker HyperPod cluster. SageMaker automatically provisions the infrastructure, deploys the model on your cluster, enables auto-scaling, and configures the SageMaker endpoint. SageMaker scales the compute resources up and down through HyperPod task governance as the traffic on model endpoints changes, and automatically publishes metrics to the HyperPod observability dashboard to provide full visibility into model performance.

You can deploy models from SageMaker JumpStart in all AWS Regions where HyperPod is available: US East (N. Virginia), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), and South America (São Paulo).

To learn more, visit SageMaker HyperPod webpage, blog, and documentation.

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Source: Amazon Web Services

 

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