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You can use describe_model_package to get the description of the specified model package.
In the response, in ModelDataUrl
parameter you'll find the Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
You can download this file and unzip it. Inside will be the model files, as output of the training.
You can check this example notebook in which we show how to use Amazon SageMaker to train a Scikit-learn Random Forest model, register it in Model Registry, and run a Batch Transform Job.
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This sounds great. Is there any documentation regarding the internal structure of the gzip file?