metadata
library_name: gliner
pipeline_tag: token-classification
license: mit
tags:
- gliner
- relation-extraction
- data-use
- v0
- alpha
datause-relation-v0
Fine-tuned GLiNER2 adapter for relation extraction in Data Use impact assessment pipeline.
Architecture: LoRA adapter for fastino/gliner2-large-v1
Relations: has_organization, used_by, has_acronym, has_timeframe, has_geography
Training data: LLM-generated synthetic + real-world PDF text
Status: v0 alpha — initial fine-tuning.
Usage
from gliner import GLiNER2
model = GLiNER2.from_pretrained("fastino/gliner2-large-v1")
model.load_adapter("ai4data/datause-relation-v0")
Pipeline Integration
Call 1b in 3-model swarm:
- Call 1: Entity extraction (
ai4data/datause-extraction) - Call 1b: Relation extraction (this model)
- Call 2: Classification (
ai4data/datause-impact-v0)