Learn how to evaluate and fine-tune an Enterprise RAG Knowledge Base using Label Studio, ChatGPT, LangChain, and Ragas metrics.
Quality data labeling, model training and model fine-tuning is critical to achieving AI/ML success. In this webinar, Bernard Lawes will talk through some of the issues that prevent data labeling programs from achieving their goals, and ways to overcome these obstacles.
Learn how to use Prompts in Label Studio to refine and automate pre-labeling with LLMs for more efficient data annotation.
LLM-as-a-Judge is an increasingly popular way to evaluate the output of AI models. But is it actually worth using? And if so, how?
Discover how to compare LLMs in Label Studio to select the best model for your data labeling tasks.
Like any AI, RAG can fail in a number of ways, which can impact your business. How do you know where your RAG is failing, and more importantly, how can you stop it before it creates problems?
Aaron Schliem, Sr. Solutions Architect at Welocalize, will talk us through the data design lifecycle - from defining the problem you’re trying to solve with data to building your data pipeline - and how to build out your annotation team within that context.
Join us for a live workshop to learn how you can easily autolabel NLP projects with Label Studio.
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Learn how to effectively evaluate multi-turn chats from your Gen AI-based chat system to unlock better performance and uncover potential issues.
Use Prompts in Label Studio to generate synthetic data for training AI models, including RAG systems, faster and more efficiently.
In this guide, you'll learn how to set up an audio labeling project in Label Studio.