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
File size: 784 Bytes
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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)**
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