README.md

metadata

license: mit
base_model:
  - gliner-community/gliner_large-v2.5
pipeline_tag: token-classification
library_name: transformers
tags:
  - ner
  - neuroscience

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:

• UBERONParcellation
• species
• preparationType
• technique
• biologicalSex

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)