Instructions to use NbAiLab/nb-roberta-base-scandi-1e4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-roberta-base-scandi-1e4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/nb-roberta-base-scandi-1e4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-roberta-base-scandi-1e4") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/nb-roberta-base-scandi-1e4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a11794d172f44e662a18502d8967f6fcceae6119c2345df8c55116471063af2a
- Size of remote file:
- 1.11 GB
- SHA256:
- 3491691116e3d7128ea47bce7bb46a7947c13226aea31d9098520d884f995fbb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.