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Montey/
dotnet-edge

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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

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

bash

pipx install uv
pipx ensurepath

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