fortran-edge

edge-maxxing-newdream-sdxl

This holds the baseline for the SDXL Nvidia GeForce RTX 4090 contest, which can be forked freely and optimized

Some recommendations are as follows:

• Installing dependencies should be done in pyproject.toml, including git dependencies
• Compiled models should be included directly in the repository(rather than compiling during loading), loading time matters far more than file sizes
• Avoid changing src/main.py, as that includes mostly protocol logic. Most changes should be in models and src/pipeline.py

For testing, you need a docker container with pytorch and ubuntu 22.04. You can download your listed dependencies with uv installed with:

pipx install uv
pipx ensurepath

You can then relock with uv lock, and then run with uv run start_inference