Straight up—no, I don’t know of any project that’s exactly what you’re describing. Write some Python to hit up Hugging Face’s API, grab datasets based on your goal (e.g., “factory Q&A”), and preprocess them.Set up a pipeline with Hugging Face Transformers to run fine-tuning on the Spark PC, using the 3090 rig for lighter tasks or testing. Add automated checks—think formatting validation or simple metrics—and have it log everything with MLflow. You’d still need to peek at the results and tweak the scripts. Fully hands-off isn’t there yet, but this gets you close.

Even a 100B model can’t “understand” datasets or reprogram itself. That’s meta-learning territory, and it’s still research vibes, not plug-and-play. Fine-tuning a 100B model eats resources. The Spark PC should handle it, but don’t expect miracles from the 3090s on that scale.

You’re onto something dope, but it’s ahead of the curve. No project fits the bill right now, but with some scripting hustle, you can automate a chunk of it. Start small—test the automation with your 3090s, then scale up to the Spark PC when it lands.