Idea on how to structure generation / annotation

[whoisjones]

Instead of having a unified generation function as we have now, we might want to adjust our repo in the future in a direction such that users can pick different approaches like:

For Generation: ZEROGEN: efficient zero-shot learning via dataset generation (paper) PROGEN: progressive dataset generation via in-context feedback (paper)

For Annotation: CALIBRATION: prompt-based zero-shot learning with calibration (paper) ...

At last, we should keep the possibility to generate datasets on their own, defining their own sampling strategy, sample information criterion, etc.