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--- |
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license: cc-by-nc-3.0 |
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language: |
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- da |
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pipeline_tag: fill-mask |
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tags: |
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- bert |
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- danish |
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widget: |
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- text: Hvide blodlegemer beskytter kroppen mod [MASK] |
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--- |
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# Danish medical BERT |
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MeDa-BERT was initialized with weights from a [pretrained Danish BERT model](https://huggingface.co/Maltehb/danish-bert-botxo) and pretrained for 48 epochs using the MLM objective on a Danish medical corpus of 123M tokens. |
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The development of the corpus and model is described further in [this paper](https://aclanthology.org/2023.nodalida-1.31/). |
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Here is an example on how to load the model in PyTorch using the [🤗Transformers](https://github.com/huggingface/transformers) library: |
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```python |
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from transformers import AutoTokenizer, AutoModelForMaskedLM |
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tokenizer = AutoTokenizer.from_pretrained("indsigt-ai/MeDa-Bert") |
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model = AutoModelForMaskedLM.from_pretrained("indsigt-ai/MeDa-Bert") |
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``` |
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### Citing |
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``` |
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@inproceedings{pedersen-etal-2023-meda, |
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title = "{M}e{D}a-{BERT}: A medical {D}anish pretrained transformer model", |
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author = "Pedersen, Jannik and |
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Laursen, Martin and |
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Vinholt, Pernille and |
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Savarimuthu, Thiusius Rajeeth", |
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booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)", |
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month = may, |
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year = "2023", |
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address = "T{\'o}rshavn, Faroe Islands", |
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publisher = "University of Tartu Library", |
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url = "https://aclanthology.org/2023.nodalida-1.31", |
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pages = "301--307", |
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} |
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``` |
