Instructions to use NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NbAiLab/nb-roberta-base-ncc-plus-scandi-2e4/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 6db1351ee3d4ce10ad6b33d572a26e58a155f1bc7647de7928f17e818736f73e
- Size of remote file:
- 1.11 GB
- SHA256:
- c285e48a9ac66478cb639b979dd8d570c725127a06b09ff90dfe4e3cca6b0e15
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.