Token Classification
SpanMarker
Safetensors
Arabic
ner
named-entity-recognition
generated_from_span_marker_trainer
Instructions to use iahlt/xlm-roberta-base-ar-ner-flat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use iahlt/xlm-roberta-base-ar-ner-flat with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("iahlt/xlm-roberta-base-ar-ner-flat") entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.") print(entities) - Notebooks
- Google Colab
- Kaggle
File size: 280 Bytes
44610e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"mask_token": {
"content": "<mask>",
"lstrip": true,
"normalized": false,
"rstrip": false,
"single_word": false
},
"pad_token": "<pad>",
"sep_token": "</s>",
"unk_token": "<unk>"
}
|