Instructions to use GroNLP/bert-base-dutch-cased-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-gronings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GroNLP/bert-base-dutch-cased-gronings")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GroNLP/bert-base-dutch-cased-gronings") model = AutoModelForMaskedLM.from_pretrained("GroNLP/bert-base-dutch-cased-gronings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e385b46e325e8a0c17d45de2e0e28c8dc512cfc259992f86bd7f186da89f0aa
- Size of remote file:
- 375 MB
- SHA256:
- d1eba0efd9d5103a634a32acea6efee56462009791afd23afc5be4a68cf09c92
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