Fine-Tuning & Model Management

eomer's default mode is zero-shot forecasting: upload your data, get predictions, no training required. That works for most use cases. But some datasets have patterns a general-purpose model can't fully capture without seeing domain-specific examples first.

Fine-tuning closes that gap. You can now take our foundation model and adapt it to your data directly from the dashboard. Upload a training set, configure hyperparameters, kick off a job. Progress streams back in real time so you can watch loss curves and validation metrics as training runs.

Once a fine-tuned model is ready, it shows up in your model registry alongside the base models. Run forecasts against it, compare results, or roll back if the fine-tuned version doesn't improve things. Everything is versioned and auditable.

We built this because several early users asked for it. Their data had strong domain-specific seasonality that the base model approximated but didn't nail. Fine-tuning on a few hundred rows made a measurable difference.