Token Classification
Transformers
PyTorch
Safetensors
xmod
named-entity-recognition
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  license: cc-by-nc-4.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: cc-by-nc-4.0
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+ datasets:
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+ - Babelscape/wikineural
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+ language:
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+ - de
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+ - fr
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+ - it
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+ - rm
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+ - multilingual
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+ widget:
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+ - text: Mein Name sei Gantenbein.
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+ example_title: "German example"
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+ inference:
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+ parameters:
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+ default_language: "de_CH"
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+ tags:
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+ - named-entity-recognition
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  ---
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+
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+ The [SwissBERT](https://huggingface.co/ZurichNLP/swissbert) model fine-tuned on the [WikiNEuRal](https://huggingface.co/datasets/Babelscape/wikineural) dataset for multilingual NER.
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+
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+ Supports German, French and Italian as supervised languages and Romansh Grischun as a zero-shot language.
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ token_classifier = pipeline(
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+ model="ZurichNLP/swissbert-ner",
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+ aggregation_strategy="simple",
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+ )
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+ ```
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+
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+ ### German example
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+ ```python
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+ token_classifier.model.set_default_language("de_CH")
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+ token_classifier("Mein Name sei Gantenbein.")
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+ ```
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+ Output:
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+ ```
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+ [{'entity_group': 'PER',
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+ 'score': 0.5002625,
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+ 'word': 'Gantenbein',
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+ 'start': 13,
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+ 'end': 24}]
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+ ```
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+
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+ ### French example
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+ ```python
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+ token_classifier.model.set_default_language("fr_CH")
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+ token_classifier("J'habite à Lausanne.")
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+ ```
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+ Output:
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+ ```
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+ [{'entity_group': 'LOC',
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+ 'score': 0.99955386,
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+ 'word': 'Lausanne',
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+ 'start': 10,
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+ 'end': 19}]
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+ ```