Introduction to Fine-Tuning Gemma 4 with Cloud Run Jobs Fine-tuning pre-trained models like Gemma 4 can be a powerful way to achieve state-of-the-art results on specific tasks, such as pet breed classification. However, training these models requires significant computational resources, particularly when using GPU acceleration. In this article, we will explore how to fine-tune Gemma 4 using Cloud Run Jobs, leveraging the NVIDIA RTX 6000 Pro GPU for serverless computing. Prerequisites Before we begin, ensure you have the following: A Google Cloud account with the Cloud Run and Cloud Storage APIs enabled The gcloud command-line tool installed and authenticated A basic understanding of Python and deep learning concepts The transformers and torch libraries installed ( pip install transformers torch ) Step 1: Prepare the Dataset First, we need a dataset for pet breed classification. For this example, we'll use the Stanford Dogs Dataset . Download the dataset and extract it to a local directory.…