Token Classification
SpanMarker
TensorBoard
Safetensors
English
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use LegionIntel/ner-document-context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use LegionIntel/ner-document-context with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("LegionIntel/ner-document-context") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f34a1efaa26bd52596929cc0ab000217bd549ac0455bf9cc416fcb295d4a314
- Size of remote file:
- 1.42 GB
- SHA256:
- 047c85f0b96269cd62e6f732644f067004eebd95af5b5d35965ae2528f13bf38
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.