overfeed.news

Deploy and evaluate models with Amazon SageMaker JumpStart

18h

Age

Published
Collected
Image: AWS Machine Learning Blog

Learn how to deploy an available model from Amazon SageMaker JumpStart, run a lightweight and repeatable performance test using the SageMaker Python SDK, and delete the endpoint when testing is complete.

Excerpt from the source

Choosing the right model for a specific application requires a practical way to test it with representative inputs. Amazon SageMaker JumpStart provides access to a broad catalog of already pretrained models. In this post, we show how to deploy an available model from SageMaker JumpStart, run a lightweight and repeatable performance test using the SageMaker Python SDK, and delete the endpoint when testing is complete. For supported models and available capacity, this workflow provides a…

Read the full article at aws.amazon.com

overfeed.news indexes and links. We publish a short excerpt — the full article stays at AWS Machine Learning Blog.

Log in to follow this source
Deploy and evaluate models with Amazon SageMaker JumpStart —…