edge-max-v3

edge-maxxing-newdream-sdxl pushed to my hf repo

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 requirements.txt to add extra 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 -r requirements.txt -e ., and then running start_inference