Oh, it seems to have worked out well. No matter which model you use, it’s better to refer to the author’s model card rather than the automatically generated upper part of the HF.
For this model, it would look something like the link below.
The format required will vary depending on the model, but as long as you make the dataset in a way that is easy for you to use, that should be fine.
Uploading and downloading to HF’s dataset repo and organizing large amounts of data is the forte of the datasets library.
However, there may be a recommended dataset format for HF Trainer.
In the end, it’s the same thing that we need to write a few lines of Python before passing it to the model.
I don’t think you need labels for use cases that don’t require labels. I don’t think you need labels for segmentation.