---
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](https://openminds.docs.om-i.org/en/v3.0/instance_libraries/terminologies.html):
- `UBERONParcellation`
- `species`
- `preparationType`
- `technique`
- `biologicalSex`

## Usage

````python
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)
````