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@@ -30,8 +30,19 @@ model = AutoModelForMaskedLM.from_pretrained("jannikskytt/MeDa-Bert")
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  ### Citing
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  ```
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- MeDa-BERT: A medical Danish pretrained transformer model,
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- Jannik Pedersen, Martin Laursen, Pernille Vinholt, and Thiusius Rajeeth Savarimuthu,
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- In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa) 2023,
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- pages 301–307, Tórshavn, Faroe Islands.
 
 
 
 
 
 
 
 
 
 
 
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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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+ abstract = "This paper introduces a medical Danish BERT-based language model (MeDa-BERT) and medical Danish word embeddings. The word embeddings and MeDa-BERT were pretrained on a new medical Danish corpus consisting of 133M tokens from medical Danish books and text from the internet. The models showed improved performance over general-domain models on medical Danish classification tasks. The medical word embeddings and MeDa-BERT are publicly available.",
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+ }
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  ```