sagemaker 3.4.1

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

06-18-2023 233 words 2 minutes 0 views

Contents

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

Stars: 2227, Watchers: 2227, Forks: 1221, Open Issues: 328

The aws/sagemaker-python-sdk repo was created 8 years ago and the last code push was 5 days ago.
The project is very popular with an impressive 2227 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 328 open issues on GitHub

fix: HyperparameterTuner to respect SourceCode.ignore_patterns
HyperParameterTuner not fetching channels from ModelTrainer
Added ISO regions for jumpstart
[Bug] Pipeline parameters (ParameterInteger, ParameterString) fail in ModelTrainer hyperparameters due to safe_serialize
fix(hf): correct HF neuronx pytorch version
Fix: Don't apply default experiment config for pipelines in non-Eurek…
Adding verl support
Feat: Feature Store in Sagemaker SDK v3
TypeError: StoredFunction.init() got an unexpected keyword argument 'hmac_key'
minor: fix import path
tensorflow: sm_drivers directory not found
fix: Add ml.p5e.48xlarge and ml.p5.48xlarge to EFA instance lists
Add ml.p5e.48xlarge to EFA instance lists in sagemaker-train and sagemaker-core
Feature store v3
fix: update inference processor from 'inf2' to 'neuronx'

See more issues on GitHub

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