Running Gemma 4 Inside a Docker Container with GPU Passthrough
The article provides a guide on running Gemma 4 inside a Docker container with GPU passthrough. It addresses common issues faced by machine learning teams when trying to reproduce setups after team members leave. The guide includes prerequisites and a step-by-step process to ensure a consistent environment for deploying Gemma 4 applications.
- ▪The guide emphasizes the importance of Docker for version control and reproducibility in machine learning projects.
- ▪It explains the relationship between CUDA libraries, the NVIDIA driver, and Docker containers.
- ▪The article outlines prerequisites for setting up Docker with GPU support, including checking the visibility of the NVIDIA GPU and ensuring the correct versions of Docker and the NVIDIA Container Toolkit.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 1069729) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Shreya Nalawade Posted on May 18 Running Gemma 4 Inside a Docker Container with GPU Passthrough #devchallenge #gemmachallenge #gemma Gemma 4 Challenge: Write about Gemma 4 Submission This is a submission for the Gemma 4 Challenge: Write About Gemma 4 Here's a situation every ML team eventually hits. Your intern gets Gemma 4 running locally. Beautiful. Fast. Impresses the standup. Then they leave for the semester. Three weeks later, nobody can reproduce the setup.
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