Instructions to use ai4data/datause-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use ai4data/datause-extraction with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("ai4data/datause-extraction") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
File size: 276 Bytes
191fab5 96b4e8b 191fab5 18addf6 191fab5 18addf6 191fab5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"adapter_type": "lora",
"adapter_version": "1.0",
"lora_r": 16,
"lora_alpha": 32.0,
"lora_dropout": 0.1,
"target_modules": [
"classifier",
"count_embed",
"count_pred",
"encoder",
"span_rep"
],
"created_at": "2026-04-06T13:46:19.060075Z"
} |