Models
This model was previously named "PubMedBERT (abstracts + full text)".
This is the pretrained model presented in SciBERT: A Pretrained Language Model for Scientific Text, which is a BERT model trained on scientific
fill-mask artifact mirrored from the HuggingFace Hub.
Note: This model was previously known as PubMedGPT 2.7B, but we have changed it due to a request from the NIH which holds the trademark for
About the Model An English Named Entity Recognition model, trained on Maccrobat to recognize the bio-medical entities (107 entities) from a given text corpus…
Model description - Intended uses and limitations - How to use - Training - Evaluation - Additional information - Author - Licensing information - Citation…
SapBERT-PubMedBERT SapBERT by Liu et al.
This is a PubMedBERT-base model fined-tuned using sentence-transformers.
BiomedCLIP is a biomedical vision-language foundation model that is pretrained on PMC-15M, a dataset of 15 million figure-caption pairs extracted from…
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or…
Model description - Intended uses and limitations - How to use - Limitations and bias - Training - Tokenization and model pretraining - Training corpora and…
A lexical baseline that scores a biomedical abstract against a fixed set of therapeutic areas.