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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vesteinn/ScandiBERT") model = AutoModelForMaskedLM.from_pretrained("vesteinn/ScandiBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - is | |
| - da | |
| - sv | |
| - 'no' | |
| - fo | |
| widget: | |
| - text: Fina lilla<mask>, jag vill inte bliva stur. | |
| - text: Nu ved jeg, at du frygter<mask> og end ikke vil nægte mig din eneste søn.. | |
| - text: Það er vorhret á<mask>, napur vindur sem hvín. | |
| - text: Ja, Gud signi<mask>, mítt land. | |
| - text: Alle dyrene i<mask> må være venner. | |
| tags: | |
| - roberta | |
| - icelandic | |
| - norwegian | |
| - faroese | |
| - danish | |
| - swedish | |
| - masked-lm | |
| - pytorch | |
| license: agpl-3.0 | |
| datasets: | |
| - vesteinn/FC3 | |
| - vesteinn/IC3 | |
| - mideind/icelandic-common-crawl-corpus-IC3 | |
| - NbAiLab/NCC | |
| - DDSC/partial-danish-gigaword-no-twitter | |
| # ScandiBERT | |
| Note note: The model has been updated on 2022-09-27 | |
| The model was trained on the data shown in the table below. Batch size was 8.8k, the model was trained for 72 epochs on 24 V100 cards for about 2 weeks. | |
| | Language | Data | Size | | |
| |-----------|---------------------------------------|--------| | |
| | Icelandic | See IceBERT paper | 16 GB | | |
| | Danish | Danish Gigaword Corpus (incl Twitter) | 4,7 GB | | |
| | Norwegian | NCC corpus | 42 GB | | |
| | Swedish | Swedish Gigaword Corpus | 3,4 GB | | |
| | Faroese | FC3 + Sosialurinn + Bible | 69 MB | | |
| Note: At an earlier date a half trained model went up here, it has since been removed. The model has since been updated. | |
| This is a Scandinavian BERT model trained on a large collection of Danish, Faroese, Icelandic, Norwegian and Swedish text. It is currently the highest ranking model on the ScandEval leaderbord https://scandeval.github.io/pretrained/ | |
| If you find this model useful, please cite | |
| ``` | |
| @inproceedings{snaebjarnarson-etal-2023-transfer, | |
| title = "{T}ransfer to a Low-Resource Language via Close Relatives: The Case Study on Faroese", | |
| author = "Snæbjarnarson, Vésteinn and | |
| Simonsen, Annika and | |
| Glavaš, Goran and | |
| Vulić, Ivan", | |
| booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)", | |
| month = "may 22--24", | |
| year = "2023", | |
| address = "Tórshavn, Faroe Islands", | |
| publisher = {Link{\"o}ping University Electronic Press, Sweden}, | |
| } | |
| ``` |