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:
- 0bc89935e9d3cf884d5cd9ff5f849693b5f482b1653e7d9c655c251718da049b
- Size of remote file:
- 440 MB
- SHA256:
- 978d8e944134dcd36f2dc83e6339a499b3179a72bd2033a794ca8cd3c9822852
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