Instructions to use wietsedv/bert-base-dutch-cased-finetuned-udlassy-pos 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-pos 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-pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-udlassy-pos") model = AutoModelForTokenClassification.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-udlassy-pos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc9c387accf5a1f5d846ddbf18dbdd4435bd78c4c83b1972ab500266fd8eb95b
- Size of remote file:
- 436 MB
- SHA256:
- e654839bfd1015071f9af14d4f7b6da318fd9de70cd5bebf6445146d925736ba
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