Create Your Own Large Language Model Playground in SageMaker Studio |…

Now you can deploy LLMs and experiment with them all in one place

Utilising large language models (LLMs) through a REST endpoint offers numerous benefits, but experimenting with them via API calls can be cumbersome. Below we can see how we can interact with a model that has been deployed to an Amazon SageMaker endpoint.

To streamline this process, it would be advantageous to develop a playground app that allows for seamless interaction with the deployed model. In this tutorial, we will achieve this by using Amazon SageMaker (SM) Studio as our all-in-one IDE and deploy a Flan-T5-XXL model to a SageMaker endpoint and subsequently create a Streamlit-based playground app that can be accessed directly within Studio.

All of the code for this tutorial is available in this GitHub repository.

Assessing and contrasting different LLMs is crucial for organisations to identify the most fitting model for their unique requirements and to…