Introduction

Hugging Face built Deep Learning Containers (DLCs) for Amazon Web Services customers to run any of their machine learning workload in an optimized environment, with no configuration or maintenance on their part. These are Docker images pre-installed with deep learning frameworks and libraries such as 🤗 Transformers, 🤗 Datasets, and 🤗 Tokenizers. The DLCs allow you to directly serve and train any models, skipping the complicated process of building and optimizing your serving and training environments from scratch.

The containers are publicly maintained, updated and released periodically by Hugging Face and the AWS team and available for all AWS customers within the AWS’s Elastic Container Registry. They can be used from any AWS service such as:

• Amazon Sagemaker AI: Amazon SageMaker AI is a fully managed machine learning (ML) platform for data scientists and developers to quickly and confidently build, train, and deploy ML models into a production-ready hosted environment.
• Amazon Bedrock: Amazon Bedrock is a fully managed service that makes high-performing foundation models (FMs) from leading AI companies and Amazon available for your use through a unified API to build generative AI applications.
• Amazon Elastic Kubernetes Service (EKS): Amazon EKS is the premiere platform for running Kubernetes clusters in the AWS cloud.
• Amazon Elastic Container Service (ECS): Amazon ECS is a fully managed container orchestration service that helps you easily deploy, manage, and scale containerized applications.
• Amazon Elastic Compute Cloud (EC2): Amazon EC2 provides on-demand, scalable computing capacity in the Amazon Web Services (AWS) Cloud.

Hugging Face DLCs are open source and licensed under Apache 2.0. Feel free to reach out on our community forum if you have any questions.