| 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 | |
| ```python | |
| 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`) | |