Instructions to use activebus/BERT-DK_laptop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use activebus/BERT-DK_laptop with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="activebus/BERT-DK_laptop")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("activebus/BERT-DK_laptop") model = AutoModelForMaskedLM.from_pretrained("activebus/BERT-DK_laptop") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 782ebbe229e9cd2c414e5cf0615a22c312d15145452d13fe8cd644fcd94d2b34
- Size of remote file:
- 440 MB
- SHA256:
- c0bad6ab3ca4e946e9fdecf3e6f09ae1eb1a795b658c5d681ad9d335089123fd
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