🧬 OpenMed ZeroShot NER Pharma XLarge 770M Specialized model for Chemical Entity Recognition Chemical entities from the BC5CDR dataset 📋 Model Overview Focused on chemical mentions in the BC5CDR domain, capturing pharmaceutical compounds and therapeutic agents in context with diseases.Enables pharmacovigilance , adverse event mining , and chemical–disease relation pipelines when paired with downstream relation extraction. OpenMed ZeroShot NER is an advanced, domain adapted Named Entity Recognition (NER) model designed specifically for medical, biomedical, and clinical text mining. Leveraging state of the art zero shot learning, this model empowers researchers, clinicians, and data scientists to extract expert level biomedical entities—such as diseases, chemicals, genes, species, and clinical findings—directly from unstructured text, without the need for task specific retraining. Built on the robust GLiNER architecture and fine tuned on curated biomedical corpora, OpenMed ZeroShot NER delivers high precision entity recognition for critical healthcare and life sciences applications. Its zero shot capability means you can flexibly define and extract any entity type relevant to your w…
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