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:
- 60f1b17b25ce9d855c2061f5d37dede8abeea1e34f788d75f0ec38dbe77996c5
- Size of remote file:
- 445 MB
- SHA256:
- b808cbeb6286696b471dc0b33a759d64adfb99ce599856fc1f3803cb49ecb10b
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