sagemaker 2.232.2

Open source library for training and deploying models on Amazon SageMaker.

06-18-2023 247 words 2 minutes 0 views

Contents

Open source library for training and deploying models on Amazon SageMaker.

2096 Stars :star:

Stars: 2096, Watchers: 2096, Forks: 1138, Open Issues: 320

The aws/sagemaker-python-sdk repo was created 6 years ago and the last code push was Yesterday.
The project is very popular with an impressive 2096 github stars!

How to Install sagemaker

You can install sagemaker using pip

pip install sagemaker

or add it to a project with poetry

poetry add sagemaker

Package Details

Author: Amazon Web Services
License: None
Homepage: None
PyPi:: https://pypi.org/project/sagemaker/
GitHub Repo:: https://github.com/aws/sagemaker-python-sdk

Classifiers

No sagemaker pypi packages just yet.

Errors

A list of common sagemaker errors.

Code Examples

Here are some sagemaker code examples and snippets.

GitHub Issues

The sagemaker package has 320 open issues on GitHub

feat: add PipelineDefinitionConfig to pipelines to toggle custom job …
feature: add SageMaker FeatureStore feature processing
fix: key prefix preventing jumpstart model repack
build(deps): bump apache-airflow from 2.6.0 to 2.6.2 in /requirements/extras
fix: Fix unclear error messages for SageMaker Pipelines
feat: Add optional monitoring_config_override parameter in suggest_baseline API
Use logger and remove print statements
feat: SDK defaults add disable profiler to createTrainingJob
feature: model registry integration to model cards to support model packages
[BUG] Metric definition is not detected
Bloomz models having task name as textgeneration1 on JumpStart
fix: Fix dependabot alert in transformers package
Unable to upgrade to new sagemaker version due to PyYAML conflict
Support Lambda - Reduce Size
feature: Add segment config for Clarify

See more issues on GitHub

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