Ah yes you’re right - silly me! In that case I wonder whether knowledge distillation would be a viable approach? The idea being that you use the existing fine-tuned NER tagger as the teacher and then initialise a student with the same model type, but a new head to accomodate the new entities.
You’ll still need a corpus involving a mix of the original entities and the new ones, but it might be that with knowledge distillation you can get by with few samples than the original corpus that was used to train the teacher.
The docs on NER are indeed a bit confusing, but there’s a very nice tutorial by Sylvain Gugger that you can use as a template: https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/token_classification.ipynb 51