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PedroDKE/dutch-ner-abb

Dutch NER model fine-tuned with weak supervision.

Base model: GroNLP/bert-base-dutch-cased

Labels (BIO): DATE, PERIOD, LOCATION, LEGAL_GROUND, ADMINISTRATIVE_BODY, MANDATARY

Quickstart

from transformers import pipeline

ner = pipeline("token-classification", model="PedroDKE/dutch-ner-abb", aggregation_strategy="simple")
print(ner("Voorbeeldtekst over de gemeenteraad op 12 maart 2024 in Gent."))

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Safetensors

Model size

0.1B params

Tensor type

F32

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