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# GLiNER-BioMed
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**GLiNER** is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoders (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
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# GLiNER-BioMed
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The model was presented in the paper [GLiNER-biomed: A Suite of Efficient Models for Open Biomedical Named Entity Recognition](https://huggingface.co/papers/2504.00676).
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The code is available at [https://github.com/ds4dh/GLiNER-biomed](https://github.com/ds4dh/GLiNER-biomed).
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**GLiNER** is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoders (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
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