from transformers import pipeline

ner = pipeline("ner", model="thomasbeste/modernbert-da-ner-base", 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

Base model: AI-Sweden-Models/ModernBERT-base
Dataset: DaNE (alexandrainst/dane) — 4,383 train / 564 val / 565 test sentences
Epochs: 10
Learning rate: 2e-5
Batch size: 16
Optimizer: AdamW (weight decay 0.01, warmup ratio 0.1)
Precision: bf16
Max sequence length: 256