Instructions to use NbAiLab/nb-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-bert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/nb-bert-large")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NbAiLab/nb-bert-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 163efa4d2f7cd827e92b7d06e1c0b51f46d94edcab1e34288e0cee7d915d0834
- Size of remote file:
- 1.42 GB
- SHA256:
- 0c2d6e3ac7cfd9bfd369a9077415f3d91910bf8cd8198f5724a6d70963acc23a
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