Generative AI is revolutionizing how we build modern applications, but for developers, it can be daunting, particularly with evaluating models, building with Gen AI, and the path to production. But, it doesn’t have to be worrisome! Join us in this session to be ahead of the curve when it comes to AI-enabled cloud-native application development.

Using container technology and open source models from Hugging Face, we’ll show how to practically integrate Gen AI in an existing application from your local development environment and ultimately deploy it onto Kubernetes. Why work with local and open-source models? From reducing cloud computing costs, keeping control of your sensitive data, and alleviating vendor-locking, it’s an increasingly popular way for developers to prototype AI applications quickly. We’ll demonstrate a sample of the whole AI journey, starting from assessing models, building applications with LLMs, and deploying/serving AI applications.

The rise of large language models (LLMs) has opened up exciting possibilities for developers looking to build intelligent applications. However, the process of adapting these models to specific use cases can be difficult, requiring deep expertise and substantial resources. In this talk, we'll introduce you to InstructLab, an open-source project that aims to make LLM tuning accessible to developers and engineers of all skill levels, on consumer-grade hardware.

We'll explore how InstructLab's innovative approach combines collaborative knowledge curation, efficient data generation, and instruction training to enable developers to refine foundation models for specific use cases. In this workshop, you’ll be provided a RHEL VM and learn how to enhance an LLM with new knowledge and capabilities for targeted applications, without needing data science expertise. Join us to explore how LLM tuning can be more accessible and democratized, empowering developers to build on the power of AI in their projects.