Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
cancer-genetics
oncology
gene-regulation
cancer-research
amino_acid
anatomical_system
cancer
cell
cellular_component
developing_anatomical_structure
gene_or_gene_product
immaterial_anatomical_entity
multi-tissue_structure
organ
organism
organism_subdivision
organism_substance
pathological_formation
simple_chemical
tissue
feat: Upload fine-tuned medical NER model OpenMed-ZeroShot-NER-Oncology-Base-220M
Browse files
README.md
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### Installation
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```bash
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pip install gliner
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```
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### Usage
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model_name = "OpenMed/OpenMed-ZeroShot-NER-Oncology-Base-220M"
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from gliner import GLiNER
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model = GLiNER.from_pretrained(
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# Example usage with default entity types
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text = "Mutations in KRAS gene drive oncogenic transformation."
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### Installation
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```bash
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pip install -q "gliner[tokenizers]"
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```
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### Usage
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model_name = "OpenMed/OpenMed-ZeroShot-NER-Oncology-Base-220M"
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from gliner import GLiNER
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model = GLiNER.from_pretrained(model_name)
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# Example usage with default entity types
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text = "Mutations in KRAS gene drive oncogenic transformation."
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