Instructions to use dbmdz/bert-base-historic-dutch-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/bert-base-historic-dutch-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/bert-base-historic-dutch-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-historic-dutch-cased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/bert-base-historic-dutch-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41b3fe6a238a0afdbe6469c4e3eb5b37ff53a41952be026f38f870d85c239317
- Size of remote file:
- 543 MB
- SHA256:
- 2d93036b0900bd30e7c9ee15ed72d74dcb79ba35387e57e88a36e2f0ad2ed124
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