Token Classification
SpanMarker
PyTorch
TensorBoard
Safetensors
multilingual
ner
named-entity-recognition
Eval Results (legacy)
Instructions to use tomaarsen/span-marker-xlm-roberta-base-multinerd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use tomaarsen/span-marker-xlm-roberta-base-multinerd with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-xlm-roberta-base-multinerd") 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 tomaarsen/span-marker-xlm-roberta-base-multinerd: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/tomaarsen/span-marker-xlm-roberta-base-multinerd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tomaarsen/span-marker-xlm-roberta-base-multinerd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tomaarsen/span-marker-xlm-roberta-base-multinerd/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 05770fd48cd64241bf68ca4340d13a6a9bb4e935b114d7d06ffe2f53271c3796
- Size of remote file:
- 1.11 GB
- SHA256:
- f3ea4133db3f6422e8683665d09ead96727287130eacbf5b2772130a40988a67
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