In part 7 of “Generative AI Foundations on AWS” from AWS Machine Learning University (MLU), AWS generative AI expert instructor Emily Webber will show you multiple options for deploying foundation models on AWS and how to optimize your model for deployment. You’ll dive deep on large model deployments containers, and learn the top configuration tips for deploying foundation models on Amazon SageMaker.
Next, you’ll review prompt engineering tips for invoking foundation models and how to use retrieval augmented generation to mitigate model hallucination. Finally, you’ll have the opportunity to deploy a foundation model on Amazon SageMaker using this this 176B BLOOM example: https://go.aws/43wav1G
Learn more about generative AI on AWS: https://go.aws/3Djhssr
Tune in to Build On Generative AI with host Emily Webber on twitch.tv/aws for even more tips and tricks: https://m.twitch.tv/videos/1723458659
Access the slides from this lesson to follow along: https://github.com/aws-samples/sagemaker-distributed-training-workshop/blob/main/slides/Generative%20AI%20Foundations%20Technical%20Deep%20Dive/1%20-%20Intro%20to%20FMs.pdf.zip
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