JumpStart Foundation Models

Amazon SageMaker JumpStart offers state-of-the-art foundation models for use cases such as content writing, code generation, question answering, copywriting, summarization, classification, information retrieval, and more. Use JumpStart foundation models to build your own generative AI solutions and integrate custom solutions with additional SageMaker features. For more information, see Getting started with Amazon SageMaker JumpStart.

A foundation model is a large pre-trained model that is adaptable to many downstream tasks and often serves as the starting point for developing more specialized models. Examples of foundation models include LLaMa-2-7b, BLOOM 176B, FLAN-T5 XL, or GPT-J 6B, which are pre-trained on massive amounts of text data and can be fine-tuned for specific language tasks.

Amazon SageMaker JumpStart onboards and maintains publicly available foundation models for you to access, customize, and integrate into your machine learning lifecycles. For more information, see Publicly available foundation models. Amazon SageMaker JumpStart also includes proprietary foundation models from third-party providers. For more information, see Proprietary foundation models.

To get started exploring and experimenting with available models, see How to use JumpStart foundation models. All foundation models are available to use programmatically with the SageMaker Python SDK. For more information, see Use foundation models with the SageMaker Python SDK.

For more information on considerations to make when choosing a model, see Model sources and license agreements.

For specifics about customization and fine-tuning foundation models, see Customize a foundation model.

For more general information on foundation models, see the paper On the Opportunities and Risks of Foundation Models.