Instructions to use proycon/bert-ner-cased-conll2002-nld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use proycon/bert-ner-cased-conll2002-nld with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="proycon/bert-ner-cased-conll2002-nld")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("proycon/bert-ner-cased-conll2002-nld") model = AutoModelForTokenClassification.from_pretrained("proycon/bert-ner-cased-conll2002-nld") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc5bdbb8065ef832816d173357404890a4966f4b705b5c085c81a8e3cc702389
- Size of remote file:
- 434 MB
- SHA256:
- 636e80ac5d3838f94baf9b23c54209917664f61d18f89d2df04d7bef32b851a2
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