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SciLake-Neuroscience-GLiNER-large
SIRIS-Lab/SciLake-Neuroscience-GLiNER-large
SciLake-Neuroscience-GLiNER-large is a token classification model from SIRIS-Lab. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
GLiNER-large model finetuned on a selection of relevant entities in the domain of neuroscience, from the openMINDS controlled terms: - UBERONParcellation - species - preparationType - technique - biologicalSex
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Public
Updated Sep 25, 2025
Repo size
1.8 GB
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Sep 25, 2025
- Updated
- Sep 25, 2025
- SHA
- 71e0a65e
Try a prompt
Base models
Model card
From the Hugging Face model README
SciLake Neuroscience named-entity recognition
GLiNER-large model finetuned on a selection of relevant entities in the domain of neuroscience, from the openMINDS controlled terms:
UBERONParcellationspeciespreparationTypetechniquebiologicalSex
Usage
from gliner import GLiNER
LABELS = ['UBERONParcellation', 'species', 'preparationType', 'technique', 'biologicalSex']
THRESHOLD = xxx # choose your threshold
model = GLiNER.from_pretrained('SIRIS-Lab/SciLake-Neuroscience-GLiNER-large')
entities = model.predict_entities(to_tag, labels=LABELS, threshold=THRESHOLD)
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Created
- Sep 25, 2025
- Updated
- Sep 25, 2025