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EvanD/dutch-ner-xlm-conll2003
dutch-ner-xlm-conll2003 is a token classification model from EvanD. Use it when you need labels on individual words, such as names. It is set up for transformers.
Contrary to my other models, this one is purely a repackaging of flair/ner-dutch-large but transformed back to pure huggingface pytorch for performance purposes.
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From the Hugging Face model README
Contrary to my other models, this one is purely a repackaging of flair/ner-dutch-large but transformed back to pure huggingface pytorch for performance purposes.
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("EvanD/dutch-ner-xlm-conll2003")
ner_model = AutoModelForTokenClassification.from_pretrained("EvanD/dutch-ner-xlm-conll2003")
nlp = pipeline("ner", model=ner_model, tokenizer=tokenizer, aggregation_strategy="simple")
example = "George Washington ging naar Washington"
ner_results = nlp(example)
print(ner_results)
# {
# "start_pos": 0,
# "end_pos": 17,
# "text": "George Washington",
# "score": 0.9999986886978149,
# "label": "PER"
# }
# {
# "start_pos": 28,
# "end_pos": 38,
# "text": "Washington",
# "score": 0.9999939203262329,
# "label": "LOC"
# }