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feat(client-sagemaker): Adds support for ModelDataSource in Model Packages to support unzipped models. Adds support to specify SourceUri for models which allows registration of models without mandating a container for hosting. Using SourceUri, customers can decouple the model from hosting information during registration.
* <code>CreateEndpointConfig</code> API, and then create an endpoint with the
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* <code>CreateEndpoint</code> API. SageMaker then deploys all of the containers that you
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* defined for the model in the hosting environment. </p>
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* <p>For an example that calls this method when deploying a model to SageMaker hosting services,
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* see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-deployment.html#realtime-endpoints-deployment-create-model">Create a Model (Amazon Web Services SDK for Python (Boto 3)).</a>
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* </p>
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* <p>To run a batch transform using your model, you start a job with the
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* <code>CreateTransformJob</code> API. SageMaker uses your model and your dataset to get
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* inferences which are then saved to a specified S3 location.</p>
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