Token Classification
ONNX
GLiNER
multilingual
named-entity-recognition
zero-shot
int8
dakera
ai-agent-memory
self-hosted
Instructions to use DakeraAI/gliner_multi-v2.1-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use DakeraAI/gliner_multi-v2.1-int8 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("DakeraAI/gliner_multi-v2.1-int8") 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
File size: 133 Bytes
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