Instructions to use ai4data/datause-impact-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use ai4data/datause-impact-v0 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("ai4data/datause-impact-v0") - Notebooks
- Google Colab
- Kaggle
| library_name: gliner | |
| pipeline_tag: token-classification | |
| license: mit | |
| tags: | |
| - gliner | |
| - classification | |
| - data-use | |
| - v0 | |
| - alpha | |
| # datause-impact-v0 | |
| Fine-tuned GLiNER2 adapter for multi-task classification in Data Use impact assessment pipeline. | |
| **Architecture:** LoRA adapter for `fastino/gliner2-large-v1` | |
| **Tasks:** usage, typology, purpose_action | |
| **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-impact-v0") | |
| ``` | |
| ## Pipeline Integration | |
| Call 2 in 3-model swarm: | |
| - Call 1: Entity extraction (`ai4data/datause-extraction`) | |
| - Call 1b: Relation extraction (`ai4data/datause-relation-v0`) | |
| - **Call 2: Classification (this model)** | |