Instructions to use FluidInference/gliner2-5-base-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use FluidInference/gliner2-5-base-coreml with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("FluidInference/gliner2-5-base-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
File size: 604 Bytes
368e10b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"model": "fastino/gliner2.5-base-v1",
"revision": "1a8bc24e00dc7300b9017c81d63e3dcdabb26596",
"package": "build/gliner2_base_classification_fp16_L128_K8.mlpackage",
"selected_manifest": "first eligible rows in source suite order; no gold labels used",
"counts": {
"checked": 100,
"too_many_options": 300,
"too_long": 7,
"duplicate_labels": 0,
"mismatches": 0
},
"maximum_confidence_error": 0.0029987096786499023,
"mean_confidence_error": 0.00020762801170349122,
"model_call_p50_ms": 8.819750044494867,
"model_call_p95_ms": 13.183709001168609,
"failures": []
}
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