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Amazon SageMaker Studio now integrates with Hugging Face for one-click model deployment and customization

Amazon SageMaker Studio now integrates directly with Hugging Face, allowing users to select a model and customize or deploy it within a pre-configured Studio environment in one click. New customers receive a ready-to-use environment with pre-configured permissions, while existing customers can access directly from Hugging Face.

Amazon SageMaker Studio now supports direct integration from Hugging Face, allowing users to go from discovering a model to working with it inside a fully configured Studio environment in a single click. By selecting any supported model on Hugging Face and choosing "Customize on SageMaker AI" or "Deploy on SageMaker AI," users land directly on the corresponding workflow page with the model pre-loaded and ready to use. Previously, getting from model discovery to a working environment required navigating the AWS Console to find SageMaker AI, configuring an environment, setting up IAM permissions for serverless model customization, and often requesting GPU quota increases through Service Quotas before running a first job. Now, new customers complete a standard AWS sign-up and receive a SageMaker Studio environment created in seconds with pre-configured permissions for serverless model customization jobs, including fine-tuning with custom reward functions for reinforcement learning, model evaluation, and deployment to SageMaker or Bedrock endpoints. Verified customers receive default GPU access to G5, G6, and G4dn instances across endpoint deployments, training jobs, and notebooks without requesting quota increases, and quota limit and utilization information is visible for each instance type directly inside the Studio environment. Returning customers signing in from Hugging Face or SageMaker product pages select their environment and land directly inside SageMaker Studio with the model ready to use. This feature is available in all AWS Commercial Regions where Amazon SageMaker Studio is supported.

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