Token Classification
GLiNER2
Safetensors
Indonesian
English
multilingual
extractor
sentiment-analysis
fine-tuned
lora
gliner2.5
mdeberta-v3
Instructions to use hadimaster65555/gliner25-indonesian-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use hadimaster65555/gliner25-indonesian-sentiment with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("hadimaster65555/gliner25-indonesian-sentiment") # 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
Ctrl+K