For a hands-on learning experience to develop LLM applications, join our LLM Bootcamp today. Early Bird Discount Ending Soon!
Training today’s complex AI models requires integrating multiple steps into an interconnected workflow. Modern MLOps/LLMOps tools help scale AI training by orchestrating these workflows. Effective tooling provides a reliable framework for machine learning operations by streamlining processes, increasing efficiency, and enhancing reproducibility.
In this hands-on session, we will explore how modern MLOps/LLMOps tooling can optimize AI workflows, streamline processes, and enhance reproducibility. You will learn how to fine-tune an LLM using Hugging Face, integrate it into a scalable workflow with Union.ai, and deploy it in a real-world application.
What we will cover
To follow along, you will need a free Union.ai account, a GitHub account, and a Google account for Colab. These tools will enable you to build and deploy scalable AI workflows seamlessly. By the end of this webinar, you will have a solid understanding of how to build and deploy AI workflows for LLMs, integrating them seamlessly into your MLOps stack.