GLiNER2
Safetensors
extractor
Token Classification
Zero-Shot Classification
Text Classification
relation extraction
Structured extraction
Instructions to use fastino/gliner2-multi-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use fastino/gliner2-multi-v1 with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("fastino/gliner2-multi-v1") # 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
Update README.md
#6 opened 5 days ago
by
thaooonguyennn
any port to hindi for this??
#5 opened about 1 month ago
by
iamgrootns
Export to ONNX
π 3
2
#4 opened 4 months ago
by
uasan
Languages supported and context length?
π 1
1
#2 opened 6 months ago
by
abpani1994
Supported language list
π 1
4
#1 opened 6 months ago
by
rjmehta