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:
- 5d4119656ddd148d3655efe4c0d4e549995a643b2c244010f7498c0cbade705f
- Size of remote file:
- 531 MB
- SHA256:
- 88cc47b929d21ed816d6ad8d5abea5c06ccae04a5f04f2d6b07da7d212aa18e1
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