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 [![Continuous Integration](https://github.com/autogluon/autogluon-cloud/actions/workflows/continuous_integration.yml/badge.svg)](https://github.com/autogluon/autogluon-cloud/actions/workflows/continuous_integration.yml)
 
+[AutoGluon-Cloud Documentation](https://auto.gluon.ai/cloud/stable/index.html) | [AutoGluon Documentation](https://auto.gluon.ai)
+
 AutoGluon-Cloud aims to provide user tools to train, fine-tune and deploy [AutoGluon](https://auto.gluon.ai/stable/index.html) backed models on the cloud. With just a few lines of codes, users could train a model and perform inference on the cloud without worrying about MLOps details such as resource management.
 
 Currently, AutoGluon-Cloud supports [AWS SageMaker](https://aws.amazon.com/sagemaker/) as the cloud backend.