Token Classification
SpanMarker
Safetensors
English
ner
named-entity-recognition
generated_from_span_marker_trainer
climate-change
earth-science
Eval Results (legacy)
Instructions to use P0L3/CliReNER-sciclimatebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use P0L3/CliReNER-sciclimatebert with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("P0L3/CliReNER-sciclimatebert") entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.") print(entities) - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
e2cb4fa | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:5262e5a6c466567547790fdd2f1a4fe5437fe87cfe9eb74a863c8734b053ba69
size 5905
|