Amazon Web Services

Innovating with machine learning on AWS

On AWS, you can access performant infrastructure, deployment resources, data governance solutions, and deep learning containers (DLCs) with optimized open source frameworks, so that you can focus on your machine learning tasks.

Build and Scale AI/ML on AWS

AWS offers a comprehensive suite of AI/ML tools and services that cater to every stage of the machine learning lifecycle. From model development and training to deployment and inference, AWS provides cutting-edge solutions such Amazon SageMaker as a fully-managed service for end-to-end development and deployment of models, Amazon Bedrock for building generative AI applications, custom AI accelerator chips such as AWS Trainium for training and AWS Inferentia for inference, and pre-configured environments to streamline your ML workflows. Additionally, you can explore the Registry of Open Data to discover, access, and utilize diverse datasets for your AI/ML projects. Whether you're working on large language models, generative AI, computer vision, time-series forecasting, or natural language processing, scaling your projects on AWS is easy.

Learn more about these services and others:

• Amazon SageMaker
• Amazon Bedrock
• AWS AI Chips
• AWS GPUs for Machine Learning
• AWS Deep Learning AMIs
• AWS Deep Learning Containers (DLCs)
• Artificial Intelligence on AWS
• Registry of Open Data

AWS & Hugging Face Collaboration

AWS and Hugging Face are working together to simplify and accelerate the adoption of advanced machine learning models. This collaboration offers streamlined training using Hugging Face Deep Learning Containers with SageMaker distributed training libraries, simplifying workflows with the SageMaker Python SDK for efficient model training. Deployment is made effortless through the Hugging Face Inference toolkit and DLCs, allowing users to deploy trained models on the Hugging Face Hub. Amazon SageMaker facilitates the creation of scalable endpoints with built-in monitoring and enterprise-level security. This joint effort empowers teams to move quickly from experimentation to production, leveraging cutting-edge models and scalable infrastructure to drive innovation in machine learning projects.

• Learn about Hugging Face on AWS
• Learn about Hugging Face in Amazon SageMaker
• Reference documentation for using Hugging Face with Amazon SageMaker
• Community Forum on Hugging Face

Connect, Learn, and Grow with AWS

Stay connected with the latest AWS AI/ML and open source developments:

Let's innovate together! 🎉🚀

LLM experimentation at scale using Amazon SageMaker Pipelines and MLflow

Build a Hugging Face text classification model in Amazon SageMaker JumpStart

Inference AudioCraft MusicGen models using Amazon SageMaker