Summary
Some say that the most challenging part of starting to train a machine learning model is not the math or its internal logic. Often, the biggest hurdle is setting up a proper working environment to run the model. It's not uncommon to see engineers and professors spend an entire weekend trying to install CUDA on their lab machines. This can be due to missing dependencies, skipped steps, or version incompatibilities.
I dedicated an entire chapter to covering the installation process, hoping that these detailed steps would help you avoid common pitfalls. By following these steps, you’ll be able to delve into the Stable Diffusion model and start image generation with minimum obstacles.
Furthermore, the software and packages you installed will also work for Transformer-based large language models.
In the next chapter, we will start using Stable Diffusion to generate images.
