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-scibert_scivocab_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use P0L3/CliReNER-scibert_scivocab_uncased with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("P0L3/CliReNER-scibert_scivocab_uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cf292f60939170fa95292e73c0eda738f475793d635eaf4bf46cae91773681e
- Size of remote file:
- 5.91 kB
- SHA256:
- 2f9be7b3154c06d2eafe81a83fbf2446c1e9bdedee15ed15e84bc2e088311481
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