Token Classification
SpanMarker
Safetensors
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use lambdavi/span-marker-luke-base-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use lambdavi/span-marker-luke-base-conll2003 with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("lambdavi/span-marker-luke-base-conll2003") - Notebooks
- Google Colab
- Kaggle
Tokenizer issue
#1
by tomaarsen - opened
Hello!
This is very cool - I'd love to run it myself too, but I get an issue that word_ids() is not accessible on the non-fast LukeTokenizer . Did you get around this issue somehow?
- Tom Aarsen
Hello!
First of all, thanks for your library, works great. Yeah I am going to update the model card, I encountered this problem as well, I used the RobertaTokenizer as alternative. I still have to figure out how to use the LukeTokenizer but I am working on it and I will release a v2 soon.
tokenizer = SpanMarkerTokenizer.from_pretrained("roberta-base", config=model.tokenizer.config)
model.set_tokenizer(tokenizer)
Let me know if this solved the problem.
lambdavi changed discussion status to closed