anthonyyazdaniml
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gliner-biomed-bi-large-v1.0-disease-chemical-gene-variant-species-cellline-ner

Token Classification

information-extraction

entity-recognition

biological-entities

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anthonyyazdaniml commited on May 15

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 # GLiNER-BioMed for diseases/phenotypes, chemicals, genes/gene products, sequence variants, organisms, and cell lines NER
-This model is a fine-tuned version of the bi-encoder [GLiNER-BioMed](https://huggingface.co/papers/2504.00676) large model. This model is designed to extract details about diseases/phenotypes, chemicals, genes/gene products, sequence variants, organisms, and cell lines, based on the BioRED dataset.
 One can find more details about the base GLiNER-BioMed models in the paper [GLiNER-BioMed: A Suite of Efficient Models for Open Biomedical Named Entity Recognition](https://huggingface.co/papers/2504.00676). The GLiNER-BioMed code is available at [https://github.com/ds4dh/GLiNER-biomed](https://github.com/ds4dh/GLiNER-biomed).

 # GLiNER-BioMed for diseases/phenotypes, chemicals, genes/gene products, sequence variants, organisms, and cell lines NER
+This model is a fine-tuned version of [GLiNER-BioMed-bi-large](https://huggingface.co/Ihor/gliner-biomed-bi-large-v1.0). This model is designed to extract details about diseases/phenotypes, chemicals, genes/gene products, sequence variants, organisms, and cell lines, based on the BioRED dataset.
 One can find more details about the base GLiNER-BioMed models in the paper [GLiNER-BioMed: A Suite of Efficient Models for Open Biomedical Named Entity Recognition](https://huggingface.co/papers/2504.00676). The GLiNER-BioMed code is available at [https://github.com/ds4dh/GLiNER-biomed](https://github.com/ds4dh/GLiNER-biomed).