GLiNER2
Safetensors
Token Classification
Zero-Shot Classification
Text Classification
relation extraction
Structured extraction
Instructions to use bhaskars113/113-gliner-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use bhaskars113/113-gliner-multi with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("bhaskars113/113-gliner-multi") # 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
Commit History
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Rename config.json to gliner_config.json
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Create requirements.txt
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Create handler.py
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Initial model upload
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initial commit
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