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:
- d28df7544e38273134d1e67e8a89194e4d150fd9bc981b5f30adfa22d84f7715
- Size of remote file:
- 5.91 kB
- SHA256:
- 5d8af27bcb631eccc82297bf1464036a5e1de1513028fadfc3223214fe837dd0
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