aws/sagemaker-python-sdk

Health v2 · maintenance only

Adoption not part of the score

2261 stars · 1297 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The SageMaker Python SDK is an open-source Python library for training and deploying machine learning models on Amazon SageMaker. It supports popular frameworks like PyTorch, TensorFlow, MXNet, and Hugging Face, as well as custom algorithms in Docker containers.

Use cases

• train machine learning models on AWS SageMaker
• deploy a PyTorch model as a hosted endpoint
• run Hugging Face model training in the cloud
• bring my own algorithm in a Docker container to SageMaker
• serve a TensorFlow model on AWS
• manage SageMaker training jobs from Python

When to choose

• you are already using AWS and want managed model training and hosting
• you need to train or deploy models with PyTorch, TensorFlow, MXNet, or Hugging Face on SageMaker
• you want to use Amazon's built-in optimized ML algorithms

When to avoid

• you train and deploy models entirely outside AWS
• you want a framework-agnostic local training setup without cloud dependencies
• you rely on the legacy Estimator/Model/Predictor APIs, which are removed in V3

Facets

library · maturity active

machine-learning llm-training sdk deployment machine-learning cloud-computing deep-learning developer-tools python cloud aws sagemaker model-training model-deployment mlops

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markdown · JSON · MCP: product_card(name="aws/sagemaker-python-sdk")