metadata
library_name: span-marker
tags:
- span-marker
- token-classification
- ner
- named-entity-recognition
- generated_from_span_marker_trainer
metrics:
- precision
- recall
- f1
widget: []
pipeline_tag: token-classification
language:
- ar
SpanMarker
This is a SpanMarker model that can be used for Named Entity Recognition.
Model Details
Model Description
- Model Type: SpanMarker
- Maximum Sequence Length: 512 tokens
- Maximum Entity Length: 150 words
Model Sources
- Repository: SpanMarker on GitHub
- Thesis: SpanMarker For Named Entity Recognition
Uses
Direct Use for Inference
from span_marker import SpanMarkerModel
# Download from the 🤗 Hub
model = SpanMarkerModel.from_pretrained("iahlt/xlm-roberta-base-ar-ner-flat")
entities = model.predict("None")
print(entities)
Training Details
Framework Versions
- Python: 3.10.12
- SpanMarker: 1.5.0
- Transformers: 4.35.2
- PyTorch: 2.1.0+cu121
- Datasets: 2.16.1
- Tokenizers: 0.15.1
Citation
BibTeX
@software{Aarsen_SpanMarker,
author = {Aarsen, Tom},
license = {Apache-2.0},
title = {{SpanMarker for Named Entity Recognition}},
url = {https://github.com/tomaarsen/SpanMarkerNER}
}