Instructions to use activebus/BERT-DK_rest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use activebus/BERT-DK_rest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="activebus/BERT-DK_rest")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("activebus/BERT-DK_rest") model = AutoModelForMaskedLM.from_pretrained("activebus/BERT-DK_rest") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8469639b682b44d9b8e2480449d7cede796fcbb24a5f5c66975665a8a0435715
- Size of remote file:
- 438 MB
- SHA256:
- 154d3dc7ae1f36abf43431c01c13ef51a47b7d90514547bbe1b11c2438fd21ca
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