Instructions to use ZurichNLP/swissbert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZurichNLP/swissbert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ZurichNLP/swissbert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ZurichNLP/swissbert-ner") model = AutoModelForTokenClassification.from_pretrained("ZurichNLP/swissbert-ner") - Notebooks
- Google Colab
- Kaggle
Add citation
Browse files
README.md
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'word': 'Lausanne',
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'start': 10,
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```
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'word': 'Lausanne',
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'start': 10,
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'end': 19}]
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```
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## Citation
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```bibtex
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@article{vamvas-etal-2023-swissbert,
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title={Swiss{BERT}: The Multilingual Language Model for Switzerland},
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author={Jannis Vamvas and Johannes Gra\"en and Rico Sennrich},
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year={2023},
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eprint={2303.13310},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2303.13310}
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}
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```
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