Token Classification
GLiNER
PyTorch
English
entity recognition
NER
named entity recognition
zero shot
zero-shot
Instructions to use numind/NuNER_Zero-span with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use numind/NuNER_Zero-span with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("numind/NuNER_Zero-span") 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
Commit ·
79aa539
1
Parent(s): 276c7a6
Update README.md
Browse files
README.md
CHANGED
|
@@ -53,7 +53,7 @@ for entity in entities:
|
|
| 53 |
|
| 54 |
## Fine-tuning
|
| 55 |
|
| 56 |
-
|
| 57 |
|
| 58 |
|
| 59 |
## Citation
|
|
|
|
| 53 |
|
| 54 |
## Fine-tuning
|
| 55 |
|
| 56 |
+
A fine-tuning script can be found [here](https://colab.research.google.com/drive/1fu15tWCi0SiQBBelwB-dUZDZu0RVfx_a?usp=sharing).
|
| 57 |
|
| 58 |
|
| 59 |
## Citation
|