sagemaker/pr_2709/en/tutorials/index.md

Tutorials

Pick the offering that matches how you want to work. Every tutorial is self-contained and reproducible.

Offering	Use it when	Start here
SageMaker SDK	You want full control from Python: deploy any Hub model, run custom training on managed infrastructure.	Quickstart
JumpStart	You want a curated model catalog with performant defaults, deployable in a few clicks.	Quickstart
Bedrock	You want JumpStart models behind the managed Bedrock APIs (Agents, Knowledge Bases, Guardrails).	Quickstart
EC2, ECS, and EKS	You want to run the Deep Learning Containers directly on AWS compute services.	Quickstart
Inference Endpoints	You want Hugging Face to manage the infrastructure, optimized for cost and throughput.	Guide

All offerings run the same Hugging Face Deep Learning Containers. For end-to-end recipes (TRL fine-tuning, embedding models, Inferentia2, and more), see the Examples section in the sidebar.