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:
- 9a6e2feb21501291213087aa635c8c09b60ada5be4a6eb89ffc1509d5eab188d
- Size of remote file:
- 438 MB
- SHA256:
- a38320b415a31ceb1bafe7f0a6d01e701e943caa3139518c92c5ccb5fed5bbdf
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