Token Classification
SpanMarker
PyTorch
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use Aaron-Wu/multiNERD_fine-tuned_only_English_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use Aaron-Wu/multiNERD_fine-tuned_only_English_roberta with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("Aaron-Wu/multiNERD_fine-tuned_only_English_roberta") entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.") print(entities) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Aaron-Wu/multiNERD_fine-tuned_only_English_roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Aaron-Wu/multiNERD_fine-tuned_only_English_roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aaron-Wu/multiNERD_fine-tuned_only_English_roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aaron-Wu/multiNERD_fine-tuned_only_English_roberta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- d2797b6837b997cd829f1d419c7ba439820c7caf67e26348877661228d4ac24e
- Size of remote file:
- 499 MB
- SHA256:
- 9dc93bdd5f259d2792df17836946c0030d24d300a992b2ddd7325cbef92bb381
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