Fine-Tuning Gemma 2-9B on GKE using Metaflow and Argo Workflows
This tutorial will provide instructions on how to deploy and use the Metaflow framework on GKE (Google Kubernetes Engine) and operate AI/ML workloads using Argo-Workflows.
Tag: Evaluation
Fine-tune gemma-2-9b and track as an experiment in MLFlow
In this tutorial we will fine-tune gemma-2-9b using LoRA as an experiment in MLFlow. We will deploy MLFlow on a GKE cluster and set up MLFlow to store artifacts inside a GCS bucket. In the end, we will deploy a fine-tuned model using KServe.