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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). Next, it was fine-tuned for 48 epochs with masked language modelling on a medical corpus of 123M tokens.
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The development of the model is described further in the paper:
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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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# 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). Next, it was fine-tuned for 48 epochs with masked language modelling on a Danish medical corpus of 123M tokens.
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The development of the corpus and model is described further in the paper:
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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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