# 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`
- Change `install_args.txt` to add `pip install` arguments to be used when installing the package

For testing, you need a docker container with pytorch and ubuntu 22.04,
you can download your listed dependencies with `pip install $(cat install_args.txt) -e .`, and then running `start_inference`