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
File size: 607 Bytes
0a423df | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"model": "fastino/gliner2.5-multi-v1",
"revision": "a221b77a8baf4a613b8f8652661d41fa10a5641e",
"package": "build/gliner2_multi_classification_fp32_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": 31,
"duplicate_labels": 0,
"mismatches": 0
},
"maximum_confidence_error": 8.046627044677734e-06,
"mean_confidence_error": 7.531046867370605e-07,
"model_call_p50_ms": 11.235417041461915,
"model_call_p95_ms": 19.665875006467104,
"failures": []
}
|