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