from optimum.onnxruntime import ORTModelForTokenClassification
from transformers import AutoTokenizer, pipeline

model = ORTModelForTokenClassification.from_pretrained("thomasbeste/modernbert-da-ner-base-onnx-int8")
tokenizer = AutoTokenizer.from_pretrained("thomasbeste/modernbert-da-ner-base-onnx-int8")
ner = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple")

results = ner("Jens Peter Hansen bor i København og arbejder hos Novo Nordisk.")
for entity in results:
    print(f"{entity['word']}: {entity['entity_group']} ({entity['score']:.3f})")

Training Details

See the PyTorch model card: thomasbeste/modernbert-da-ner-base