metadata
pipeline_tag: token-classification
tags:
- named-entity-recognition
- sequence-tagger-model
widget:
- text: Mit navn er Amadeus Wolfgang, og jeg bor i Berlin
inference:
parameters:
aggregation_strategy: simple
grouped_entities: true
language:
- da
xlm-roberta model trained on daner, performing 95 f1-Macro on test set.
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("EvanD/xlm-roberta-base-danish-ner-daner")
ner_model = AutoModelForTokenClassification.from_pretrained("EvanD/xlm-roberta-base-danish-ner-daner")
nlp = pipeline("ner", model=ner_model, tokenizer=tokenizer, aggregation_strategy="simple")
example = "Mit navn er Amadeus Wolfgang, og jeg bor i Berlin"
ner_results = nlp(example)
print(ner_results)