SageMaker AI plugin: what it installs and how to add it

The plugin supports end-to-end model customisation workflows on Amazon SageMaker AI, from defining a use case and preparing datasets to selecting fine-tuning methods, training models, evaluating results, and configuring deployments. It also provides guidance for Amazon SageMaker HyperPod cluster operations, including remote access, version checks, diagnostics, and debugging.

Reach for it when developing or operating AI and machine learning workloads on AWS. Its skills cover dataset evaluation and transformation, model selection, fine-tuning, deployment, and HyperPod troubleshooting across nodes, networking, performance, and Slurm.

What's inside

• 19 skills, including dataset-evaluation, finetuning, model-deployment, and HyperPod debugging skills
• 1 MCP server
• 0 slash commands, agents, or hooks