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:
- a6e82d088cc085096ae710c7d5c7e21c207190d2efc481e6ddca160e73684737
- Size of remote file:
- 4.66 MB
- SHA256:
- 8a29f0b4c39fa3a28eb565a9e759294538877e331258bb7a8dacfc078c728326
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