edge-maxxing-sep-d4 / README.md
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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