Instructions to use NAMAA-Space/gliner_arabic-v2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use NAMAA-Space/gliner_arabic-v2.1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("NAMAA-Space/gliner_arabic-v2.1") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -6,6 +6,7 @@ language:
|
|
| 6 |
base_model:
|
| 7 |
- urchade/gliner_large-v2
|
| 8 |
pipeline_tag: token-classification
|
|
|
|
| 9 |
tags:
|
| 10 |
- GLiNER
|
| 11 |
- Arabic
|
|
|
|
| 6 |
base_model:
|
| 7 |
- urchade/gliner_large-v2
|
| 8 |
pipeline_tag: token-classification
|
| 9 |
+
library_name: gliner
|
| 10 |
tags:
|
| 11 |
- GLiNER
|
| 12 |
- Arabic
|