Instructions to use GroNLP/bert-base-dutch-cased-upos-alpino-gronings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/bert-base-dutch-cased-upos-alpino-gronings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="GroNLP/bert-base-dutch-cased-upos-alpino-gronings")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("GroNLP/bert-base-dutch-cased-upos-alpino-gronings") model = AutoModelForTokenClassification.from_pretrained("GroNLP/bert-base-dutch-cased-upos-alpino-gronings") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d956fa1381640ea0fd422eb20620476ff52dba196cc6dffb2e1f6b46a81ad1d
- Size of remote file:
- 373 MB
- SHA256:
- ef0c83e6630cce10077725fe69c31363a4f8f0290580e9cfd05b13dd16ee34ad
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