🔥 What's that biomedical model that got 170,763 downloads last month on HuggingFace?! Well, the paper is finally published! #BioLORD
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🔥 What's that biomedical model that got 170,763 downloads last month on HuggingFace?! Well, the paper is finally published! #BioLORD
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📰 Read our article in the Journal of the American Medical Informatics Association:
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📰 Read our article in the Journal of the American Medical Informatics Association:
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https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocae029/7614965
https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocae029/7614965
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📝
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📝
TLDR:
`TLDR:`
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 BioLORD-2023 is a series of semantic language models for the biomedical domain, capable of representing clinical concepts and sentences in a semantic space aligned with human preferences. Our new multilingual version supports 50+ languages and is further finetuned on 7 European languages. These models were trained contrastively and through distillations, using a corpus unifying in the same latent space the concept names of biomedical concepts and their descriptions. For concepts which didn't have a description written by humans in UMLS, we use information contained in the SnomedCT knowledge graph and the capabilities of ChatGPT to generate synthetic data and improve our results.
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 BioLORD-2023 is a series of semantic language models for the biomedical domain, capable of representing clinical concepts and sentences in a semantic space aligned with human preferences. Our new multilingual version supports 50+ languages and is further finetuned on 7 European languages. These models were trained contrastively and through distillations, using a corpus unifying in the same latent space the concept names of biomedical concepts and their descriptions. For concepts which didn't have a description written by humans in UMLS, we use information contained in the SnomedCT knowledge graph and the capabilities of ChatGPT to generate synthetic data and improve our results.
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🤗 Access our models from the HuggingFace hub, including the new 2023-C and 2023-S variants:
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🤗 Access our models from the HuggingFace hub, including the new 2023-C and 2023-S variants:
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https://huggingface.co/FremyCompany/BioLORD-2023
FremyCompany/BioLORD-2023
model
resource
https://huggingface.co/FremyCompany/BioLORD-2023
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https://huggingface.co/FremyCompany/BioLORD-2023-M
FremyCompany/BioLORD-2023-M
model
resource
https://huggingface.co/FremyCompany/BioLORD-2023-M
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https://huggingface.co/FremyCompany/BioLORD-2023-S
FremyCompany/BioLORD-2023-S
model
resource
https://huggingface.co/FremyCompany/BioLORD-2023-S
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https://huggingface.co/FremyCompany/BioLORD-2023-C
FremyCompany/BioLORD-2023-C
model
resource
https://huggingface.co/FremyCompany/BioLORD-2023-C
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🔥 What's that biomedical model that got 170,763 downloads last month on HuggingFace?! Well, the paper is finally published! #BioLORD

📰 Read our article in the Journal of the American Medical Informatics Association:
https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocae029/7614965

📝`TLDR:` BioLORD-2023 is a series of semantic language models for the biomedical domain, capable of representing clinical concepts and sentences in a semantic space aligned with human preferences. Our new multilingual version supports 50+ languages and is further finetuned on 7 European languages. These models were trained contrastively and through distillations, using a corpus unifying in the same latent space the concept names of biomedical concepts and their descriptions. For concepts which didn't have a description written by humans in UMLS, we use information contained in the SnomedCT knowledge graph and the capabilities of ChatGPT to generate synthetic data and improve our results.

🤗 Access our models from the HuggingFace hub, including the new 2023-C and 2023-S variants:
https://huggingface.co/FremyCompany/BioLORD-2023
https://huggingface.co/FremyCompany/BioLORD-2023-M
https://huggingface.co/FremyCompany/BioLORD-2023-S
https://huggingface.co/FremyCompany/BioLORD-2023-C

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ilGawo cdevelder osanseviero katielink julien-c clem macadeliccc UMCU danielhanchen samusenps yxxsgdmn pdelobelle
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clem Concor drak-hf samusenps
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Bram van Es
UMCU
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