This document is relevant for: Inf1, Inf2, Trn1, Trn2

Amazon SageMaker#

Amazon SageMaker is a fully managed machine learning (ML) platform that streamlines the end-to-end ML workflow at scale. AWS Neuron integrates with Amazon SageMaker to provide optimized performance for ML workloads on AWS Inferentia and AWS Trainium chips.

SageMaker JumpStart#

Use Amazon SageMaker JumpStart to train and deploy models using Neuron. SageMaker JumpStart is an ML hub that accelerates model selection and deployment. It provides support for fine-tuning and deploying popular models such as Meta’s Llama family of models. Users can customize pre-trained models with their data and easily deploy them.

SageMaker HyperPod#

Use Amazon SageMaker HyperPod to streamline ML infrastructure setup and optimization with AWS Neuron. SageMaker HyperPod leverages pre-configured distributed training libraries to split workloads across numerous AI accelerators, enhancing model performance. HyperPod ensures uninterrupted training through automatic checkpointing, fault detection, and recovery.

SageMaker Training#

Amazon SageMaker Model Training reduces the time and cost to train and tune ML models at scale without the need to manage infrastructure.

SageMaker Inference#

With Amazon SageMaker , you can start getting predictions, or inferences, from your trained ML models. SageMaker provides a broad selection of ML infrastructure and model deployment options to help meet all your ML inference needs.

This document is relevant for: Inf1, Inf2, Trn1, Trn2