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:
- 2dd3ecb979f3d5c9c23d3477251cd0071523bab687c72f425aadae5eb3119250
- Size of remote file:
- 9.36 kB
- SHA256:
- ff87c913a2c9f49905445f4b66fdfb9cd61b163aa3e945d1cfb0886c0bfae773
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