Instructions to use FluidInference/gliner2-5-multi-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use FluidInference/gliner2-5-multi-coreml with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("FluidInference/gliner2-5-multi-coreml") # 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
24 days ago
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Set base_model to fastino/gliner2.5-multi-v1
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27 days ago
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Document ANE placement across all FP16 extraction stages
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Add validated W8 extraction packages and ANE profiling for multi
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Document materialized Hub downloads for Core ML packages
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Add validated asymmetric embedding W8 classification option
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Add validated GLiNER2 extraction Core ML stages
Verified signatureFP32 full extraction stages with selected native parity; base also includes FP16 with documented confidence drift. Classification artifacts remain available.fcf4209 -
Publish GLiNER2.5 multilingual Core ML classification exports
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