Instructions to use FluidInference/gliner2-5-small-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use FluidInference/gliner2-5-small-coreml with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("FluidInference/gliner2-5-small-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: 606 Bytes
55bd028 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"model": "fastino/gliner2.5-small-v1",
"revision": "7e6f537f10337497069276892a5ef435028252ce",
"package": "build/gliner2_small_classification_embedding_w8_L128_K8.mlpackage",
"selected_manifest": "first eligible rows in source suite order; no gold labels used",
"counts": {
"checked": 14,
"too_many_options": 0,
"too_long": 6,
"duplicate_labels": 0,
"mismatches": 0
},
"maximum_confidence_error": 0.01684504747390747,
"mean_confidence_error": 0.003918428506170001,
"model_call_p50_ms": 6.101625040173531,
"model_call_p95_ms": 8.792000007815659,
"failures": []
}
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