AWS – Amazon SageMaker introduces one-click model inference and fine-tuning for Hugging Face models in Amazon SageMaker JumpStart

Building on the Hugging Face deep learning containers released earlier this year, Amazon SageMaker is now making it even easier to deploy and fine-tune the state-of-the-art natural language processing models (NLP) with just a few clicks using Amazon SageMaker JumpStart. Amazon SageMaker JumpStart helps you quickly and easily get started with machine learning (ML). SageMaker JumpStart provides a set of solutions for the most common use cases that can be deployed readily with just a few clicks, and supports one-click deployment and fine-tuning of popular open source models such as natural language processing, object detection, and image classification models. These solutions are fully customizable and showcase the use of AWS CloudFormation templates and reference architectures so you can accelerate your ML journey. SageMaker JumpStart is also integrated in Amazon SageMaker Studio, our fully integrated development environment (IDE) for ML, making it intuitive to discover models, solutions, and more.

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