How to fine-tune LLMs with Kubeflow Training Operator

The article provides an in-depth guide on how to fine-tune large language models (LLMs) using the Kubeflow Training Operator in a Red Hat OpenShift environment. It covers prerequisites, setup, configuration, and steps to execute distributed training jobs, leveraging open-source tools like Hugging Face's SFT Trainer and PyTorch. The guide also discusses best practices, potential improvements, and deployment options for serving the fine-tuned models.