Resources for using Chainer with Amazon SageMaker AI

You can use SageMaker AI to train and deploy a model using custom Chainer code. The SageMaker AI Python SDK Chainer estimators and models and the SageMaker AI open-source Chainer container make writing a Chainer script and running it in SageMaker AI easier. The following section provides reference material you can use to learn how to use Chainer with SageMaker AI.

What do you want to do?

I want to train a custom Chainer model in SageMaker AI.

For a sample Jupyter notebook, see the Chainer example notebooks in the Amazon SageMaker AI Examples GitHub repository.

For documentation, see Train a Model with Chainer.

I have a Chainer model that I trained in SageMaker AI, and I want to deploy it to a hosted endpoint.

For more information, see Deploy Chainer models.

I have a Chainer model that I trained outside of SageMaker AI, and I want to deploy it to a SageMaker AI endpoint

For more information, see Deploy Endpoints from Model Data.

I want to see the API documentation for Amazon SageMaker Python SDK Chainer classes.

For more information, see Chainer Classes.

I want to find information about SageMaker AI Chainer containers.

For more information, see the SageMaker AI Chainer Container GitHub repository.

For information about supported Chainer versions, and for general information about writing Chainer training scripts and using Chainer estimators and models with SageMaker AI, see Using Chainer with the SageMaker Python SDK.