FMS HF Tuning is an open source package by IBM that leverages Supervised Fine-tuning Trainer from HuggingFace to support multiple tuning techniques for LLMs. We will give an overview of the tuning techniques available and demonstrate how the library can be utilized from a Jupyter notebook from the Open Data Hub platform.

The session will include:
- Introduction into fms-hf-tuning, when, why and where you can use it.
- Architectural overview of how it fits into the Open Data Hub and Red Hat OpenShift AI platform.
- Exploring different tuning techniques like Low-rank adaptation (LoRA), prompt tuning, fine tuning, and inference.
- Deploy and run production ready LLM model tuning and inference on ODH.

Attendees will leave with a greater understanding of the complexity and benefits of LLM tuning, and the open source tools and platforms available that they can leverage to improve their AI solutions.