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: 1,214 Bytes
368e10b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | {
"source_model": "fastino/gliner2.5-base-v1",
"source_revision": "1a8bc24e00dc7300b9017c81d63e3dcdabb26596",
"package": "build/gliner2_base_classification_fp16_L128_K8.mlpackage",
"package_bytes": 388981604,
"native_total_parameters": 193581591,
"exported_parameters": 184945921,
"wrapper_max_logit_error": 2.384185791015625e-07,
"coremltools": "9.0",
"torch": "2.7.0",
"cases": [
{
"text": "The rocket launched successfully.",
"native_label": "science",
"coreml_label": "science",
"native_confidence": 0.9931463003158569,
"coreml_confidence": 0.9930862188339233,
"absolute_confidence_error": 6.008148193359375e-05
},
{
"text": "The team won the football championship.",
"native_label": "sports",
"coreml_label": "sports",
"native_confidence": 0.9999978542327881,
"coreml_confidence": 0.9999977350234985,
"absolute_confidence_error": 1.1920928955078125e-07
},
{
"text": "The budget was approved by parliament.",
"native_label": "politics",
"coreml_label": "politics",
"native_confidence": 1.0,
"coreml_confidence": 1.0,
"absolute_confidence_error": 0.0
}
]
}
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