Fine-tune your own decision model and publish it

The decision

Whatever your data decides. Any labelled set where each example maps to one of a few answers works: ticket queues, review sentiment, spam or not, product categories.

How to build it

1. pip install systemonemodels, then systemone run studio opens System One Studio on your Mac, Windows or Linux machine.
2. Load your CSV and pick the question and its options.
3. Choose LoRA, DoRA, rsLoRA or LoRA+ and train. The studio scores the fine-tune against the base on held-out rows.
4. Publish to your namespace in one click, with the evaluation attached.

Make it better

Write up what you measured: which method won, how many examples it took, and how the calibration changed. Then submit the model to Builds.