Keyboard shortcuts

Press ← or → to navigate between chapters

Press S or / to search in the book

Press ? to show this help

Press Esc to hide this help

The Dockerized Workflow

To eliminate environment-related issues and ensure perfect reproducibility, the entire project is containerized.

  • gemma-trainer (Dockerfile): This is the primary container for training and inference. It packages the Python environment, CUDA, and all necessary libraries from requirements.txt. By mounting local directories as volumes, we can iterate on code locally and execute it within the consistent container environment.
  • gguf-converter (Dockerfile.convert): The GGUF conversion process requires cmake and other build tools to compile llama.cpp. To avoid bloating our main training image, we isolate these dependencies in a separate, dedicated container. This separation of concerns is a best practice for maintaining lean and specialized environments.