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
Update README.md
Browse files
README.md
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@@ -22,6 +22,9 @@ This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that ca
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## Model Details
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### Model Description
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- **Model Type:** SpanMarker
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<!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
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- **Repository:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER)
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## Model Details
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Details are here - https://iahlt.github.io/arabic_ner/
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### Model Description
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- **Model Type:** SpanMarker
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<!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Tags
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```
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ANG - Any named language (Hebrew, Arabic, English, French, etc.)
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DUC - A branded product, objects, vehicles, medicines, foods, etc. (Apple, BMW, Coca-Cola, etc.)
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EVE - Any named event (Olympics, World Cup, etc.)
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FAC - Any named facility, building, airport, etc. (Eiffel Tower, Ben Gurion Airport, etc.)
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GPE - Geo-political entity, nation states, counties, cities, etc.
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INFORMAL - Informal language (slang)
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LOC - Non-GPE locations, geographical regions, mountain ranges, bodies of water, etc.
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ORG - Companies, agencies, institutions, political parties, etc.
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PER - People, including fictional.
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TIMEX - Time expression, absolute or relative dates or periods.
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TTL - Any named title, position, profession, etc. (President, Prime Minister, etc.)
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WOA - Any named work of art (books, movies, songs, etc.)
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MISC - Miscellaneous entities, that do not belong to the previous categories
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```
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### Model Sources
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- **Repository:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER)
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