Instructions to use NbAiLab/nb-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/nb-bert-base")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NbAiLab/nb-bert-base", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
metadata
language: 'no'
license: cc-by-4.0
tags:
- norwegian
- bert
pipeline_tag: fill-mask
widget:
- text: På biblioteket kan du [MASK] en bok.
- text: Dette er et [MASK] eksempel.
- text: Av og til kan en språkmodell gi et [MASK] resultat.
- text: >-
Som ansat får du [MASK] for at bidrage til borgernes adgang til dansk
kulturarv, til forskning og til samfundets demokratiske udvikling.
- Release 1.1 (March 11, 2021)
- Release 1.0 (January 13, 2021)
NB-BERT-base
Description
NB-BERT-base is a general BERT-base model built on the large digital collection at the National Library of Norway.
This model is based on the same structure as BERT Cased multilingual model, and is trained on a wide variety of Norwegian text (both bokmål and nynorsk) from the last 200 years.
Intended use & limitations
The 1.1 version of the model is general, and should be fine-tuned for any particular use. Some fine-tuning sets may be found on GitHub, see
Training data
The model is trained on a wide variety of text. The training set is described on
More information
For more information on the model, see