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-EnvironmentalBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use P0L3/CliReNER-EnvironmentalBERT-base with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("P0L3/CliReNER-EnvironmentalBERT-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed9040763ece68cbbbf54bfd43db8395ff94dbba75a6cf5b5a234722f604b71e
- Size of remote file:
- 329 MB
- SHA256:
- 3d04b724795b3d2acc21502bda78844bcc4a82405ad4f3f802d8f4e173bdf5e8
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