Token Classification
SpanMarker
PyTorch
TensorBoard
Safetensors
English
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use tomaarsen/span-marker-bert-base-acronyms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use tomaarsen/span-marker-bert-base-acronyms with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-acronyms") - Notebooks
- Google Colab
- Kaggle
Update model id in usage snippet
Browse files
README.md
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from span_marker import SpanMarkerModel
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# Download from the 🤗 Hub
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model = SpanMarkerModel.from_pretrained("tomaarsen/
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# Run inference
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entities = model.predict("Compression algorithms like Principal Component Analysis (PCA) can reduce noise and complexity.")
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```
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from span_marker import SpanMarkerModel
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# Download from the 🤗 Hub
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model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-acronyms")
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# Run inference
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entities = model.predict("Compression algorithms like Principal Component Analysis (PCA) can reduce noise and complexity.")
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```
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