Instructions to use GroNLP/bert-base-dutch-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/bert-base-dutch-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GroNLP/bert-base-dutch-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GroNLP/bert-base-dutch-cased") model = AutoModelForMaskedLM.from_pretrained("GroNLP/bert-base-dutch-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c3e9ed7eb2535f1c1bdee4159a79eeb47b91fd55c0da262d1dde2ba728d4c02
- Size of remote file:
- 437 MB
- SHA256:
- 5ffe408c7eea0ffee4c257c6028f8c98146967e3ac3db51dba8e2bc8a4abddf5
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