Instructions to use wietsedv/bert-base-dutch-cased-finetuned-udlassy-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wietsedv/bert-base-dutch-cased-finetuned-udlassy-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wietsedv/bert-base-dutch-cased-finetuned-udlassy-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-udlassy-ner") model = AutoModelForTokenClassification.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-udlassy-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ad1ede08957f4feaae6276d5ca93abeeff90b0e9a7e5132819d41e433ce3120
- Size of remote file:
- 434 MB
- SHA256:
- 11e788a07a62840fafe74e12fe3a99fee79f51a283c2ca8ff185761ccae6422e
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