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  ---
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- language: en
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-
 
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  tags:
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  - biomedical
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- - lexical-semantics
 
 
 
 
 
 
 
 
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  datasets:
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  - UMLS
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  **[news]** A cross-lingual extension of SapBERT will appear in the main onference of **ACL 2021**! <br>
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  **[news]** SapBERT will appear in the conference proceedings of **NAACL 2021**!
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  ### SapBERT-PubMedBERT
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- SapBERT by [Liu et al. (2020)](https://arxiv.org/pdf/2010.11784.pdf). Trained with [UMLS](https://www.nlm.nih.gov/research/umls/licensedcontent/umlsknowledgesources.html) 2020AA (English only), using [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) as the base model. Please use [CLS] as the representation of the input.
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  ### Citation
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  ```bibtex
 
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  ---
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+ license: apache-2.0
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+ language:
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+ - en
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  tags:
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  - biomedical
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+ - lexical semantics
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+ - bionlp
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+ - biology
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+ - science
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+ - embedding
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+ - entity linking
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+ ---
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+ ---
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+
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  datasets:
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  - UMLS
 
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  **[news]** A cross-lingual extension of SapBERT will appear in the main onference of **ACL 2021**! <br>
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  **[news]** SapBERT will appear in the conference proceedings of **NAACL 2021**!
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+ ### Expected input and output
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+ The input should be a string of biomedical entity names, e.g., "covid infection" or "Hydroxychloroquine". The [CLS] embedding of the last layer is regarded as the output.
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+
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  ### SapBERT-PubMedBERT
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+ SapBERT by [Liu et al. (2020)](https://arxiv.org/pdf/2010.11784.pdf). Trained with [UMLS](https://www.nlm.nih.gov/research/umls/licensedcontent/umlsknowledgesources.html) 2020AA (English only), using [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) as the base model.
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  ### Citation
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  ```bibtex