Comment by elgertam

> With BERT, you need a large, labeled dataset, and you have to train/fine-tune the model.

BERT requires a huge corpus, but it isn't labeled. BERT is trained through self-supervised learning using mask tokens and next sentence prediction. Fine-tuning is useful for specific tasks, but isn't absolutely essential for the model to function.