Fine-Tuning ESM2
This sample walks through setting up a Google Cloud GKE environment to fine-tune ESM2 (Evolutionary Scale Modeling) using NVIDIA BioNeMo Framework 2.0
Tag: Fine-Tuning
Fine-tuning Gemma 3-1B-it on L4
This tutorial guides you through fine-tuning the Gemma 3-1B-it language model on Google Kubernetes Engine (GKE) using L4 GPU, leveraging Parameter Efficient Fine Tuning (PEFT) and LoRA. It covers setting up a GKE cluster, containerizing the fine-tuning code, running the fine-tuning job, and uploading the resulting model to Hugging Face. Finally, it demonstrates how to deploy and interact with the fine-tuned model using vLLM on GKE.
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.
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.