Tutorials

OpenAI’s new Structured Outputs feature allows you to ensure outputs conform to a defined JSON structure. In this blog, we’ll explore how to leverage this feature for various labeling tasks.

In this article, we want to demonstrate a method of curating large datasets to reduce but not remove the cost for curating a high quality medical Q&A dataset in Label Studio and fine-tuning Llama 3 on this data.

This article is part of a longer series that will teach you how to develop and optimize a question answering (QA) system using Retrieval-Augmented Generation (RAG) architecture. In this tutorial, we are going to show you how to create a generator that builds responses based on those documents.

In this introduction to our tutorial series on optimizing RAG pipelines, we'll introduce an example question answering (QA) system leveraging a Retrieval-Augmented Generation (RAG) architecture and outline three methods for optimizing your RAG pipeline utilizing Label Studio.