Fill-Mask
Transformers
PyTorch
Safetensors
xlm-roberta
roberta
icelandic
norwegian
faroese
danish
swedish
masked-lm
Instructions to use vesteinn/ScandiBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vesteinn/ScandiBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vesteinn/ScandiBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vesteinn/ScandiBERT") model = AutoModelForMaskedLM.from_pretrained("vesteinn/ScandiBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vesteinn/ScandiBERT: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/vesteinn/ScandiBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vesteinn/ScandiBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vesteinn/ScandiBERT/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- b866d649bce2fb83b7183cbe539f58b5ae61d09bb1b7de926b75b697f091a58e
- Size of remote file:
- 498 MB
- SHA256:
- 8e43b0598333ac79032964480c450dbd884cdba70c2349439333c86a1252ae22
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