SpanMarker for Named Entity Recognition
This is a SpanMarker model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses prajjwal1/bert-tiny as the underlying encoder.
Note
This model is primarily used for efficient tests on the SpanMarker GitHub repository.
Usage
To use this model for inference, first install the span_marker
library:
pip install span_marker
You can then run inference with this model like so:
from span_marker import SpanMarkerModel
# Download from the 🤗 Hub
model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-tiny-fewnerd-coarse-super")
# Run inference
entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
See the SpanMarker repository for documentation and additional information on this library.
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Model tree for tomaarsen/span-marker-bert-tiny-fewnerd-coarse-super
Base model
prajjwal1/bert-tinyDataset used to train tomaarsen/span-marker-bert-tiny-fewnerd-coarse-super
Evaluation results
- F1 on coarsegrained, supervised FewNERDtest set self-reported0.708
- Precision on coarsegrained, supervised FewNERDtest set self-reported0.738
- Recall on coarsegrained, supervised FewNERDtest set self-reported0.681