Token Classification
SpanMarker
TensorBoard
Safetensors
Hebrew
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use iahlt/span-marker-xlm-roberta-base-nemo-mt-he with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use iahlt/span-marker-xlm-roberta-base-nemo-mt-he with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("iahlt/span-marker-xlm-roberta-base-nemo-mt-he") entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.") print(entities) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from iahlt/span-marker-xlm-roberta-base-nemo-mt-he: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/iahlt/span-marker-xlm-roberta-base-nemo-mt-he/resolve/a12a6aeed278255cd3eeea7510e3d9bc7fe3103d/tokenizer.json
- Command line
-
hf download hf://iahlt/span-marker-xlm-roberta-base-nemo-mt-he@a12a6aeed278255cd3eeea7510e3d9bc7fe3103d/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/iahlt/span-marker-xlm-roberta-base-nemo-mt-he/resolve/a12a6aeed278255cd3eeea7510e3d9bc7fe3103d/tokenizer.json
17.1 MB
- Xet hash:
- 093f6d927e3e07916c9bc4b0e92bade0192f80e45af21aa0ac8ebb6ff73ff2dd
- Size of remote file:
- 17.1 MB
- SHA256:
- 0898477c2e1c55b21fd4fdfce81f2e2bbf7eda740fa9fe21ef23cb36a315ac82
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