Using LLMs in Amazon SageMaker Jumpstart using SQL statements
In this recipe, you’ll explore how to use LLMs for tasks like sentiment analysis directly within Amazon Redshift by leveraging the integration with Amazon SageMaker Jumpstart. Amazon Redshift ML allows you to create ML models using SQL commands, and now, with LLM support, you can tap into powerful pre-trained models for text processing.
By following this recipe, you’ll learn how to deploy an LLM through SageMaker Jumpstart, connect it to Redshift ML, and perform advanced natural language processing tasks like sentiment classification on your data—all without the need to manage complex ML pipelines. This integration simplifies the use of generative AI for extracting insights from unstructured data in Redshift.
Getting ready
To complete this recipe, you will need:
- An Amazon Redshift data warehouse deployed in the AWS Region eu-west-1
- Amazon Redshift data warehouse admin user...
