AI is happening. The future is updating.OpenMed-ZeroShot-NER-DNA-Tiny-60M
**Specialized model for Biomedical Entity Recognition - Proteins, DNA, RNA, cell lines, and cell types** Targets **molecular biology entities**: proteins, DNA/RNA, cell lines, and cell types in biomedical research content.Great for **pathway curation**, **molecular interaction mining**, and **omics-aware information 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.
**Specialized model for Biomedical Entity Recognition - Proteins, DNA, RNA, cell lines, and cell types** Targets **molecular biology entities**: proteins, DNA/RNA, cell lines, and cell types in biomedical research content.Great for **pathway curation**, **molecular interaction mining**, and **omics-aware information 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.