Fine-Tuning Gemma 4 with Cloud Run Jobs: Unlocking Serverless GPU Power with NVIDIA RTX 6000 Pro for Pet Breed Classification

Introduction

In this article, we will explore how to fine-tune a pre-trained Gemma 4 model for pet breed classification using Cloud Run Jobs and NVIDIA RTX 6000 Pro GPUs. Gemma 4 is a powerful AI model that can be used for various computer vision tasks, including image classification, object detection, and segmentation.

Prerequisites

Before we begin, make sure you have the following:

• A Google Cloud account with a project created
• The gcloud command-line tool installed
• The pip package manager installed
• A basic understanding of Python and machine learning concepts

Step 1: Create a New Cloud Run Service

To create a new Cloud Run service, run the following command:

gcloud run services create pet-breed-classifier --platform managed --region us-central1 --allow-unauthenticated

This will create a new Cloud Run service with the name pet-breed-classifier in the us-central1 region.

Step 2: Create a New Cloud Run Job

To create a new Cloud Run job, run the following command:

gcloud run jobs create pet-breed-classifier-job --platform managed --region us-central1 --image gcr.io/[PROJECT_ID]/pet-breed-classifier

Replace [PROJECT_ID] with your actual Google Cloud project ID.

Step 3: Create a Dockerfile

Create a new file named Dockerfile with the following contents:

dockerfile
FROM gcr.io/cloudrun/hello-go

# Install dependencies
RUN apt-get update && apt-get install -y \
    git \
    curl \
    wget \
    unzip \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
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    libopenblas-dev \
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    libopenblas-dev \
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    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
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    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
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    libatlas-base-dev \
    libopenblas-dev \
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    libopenblas-dev \
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    libblas-dev \
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    libopenblas-dev \
    liblapack-dev \
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    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
    libopenblas-dev \
    liblapack-dev \
    libblas-dev \
    libatlas-base-dev \
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    liblapack-dev \
    libblas-dev \
    lib

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