| This biomedical language model uses a specialized biomedical tokenizer which is more closely aligned with human-morphological judgements than previous biomedical tokenizers such as PubMedBERT. | |
| Details about our tokenizer design, pre-training procedure and downstream results can be found in our [BioNLP @ ACL 2023 paper](http://arxiv.org/pdf/2306.17649.pdf) | |
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| license: apache-2.0 | |
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