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 GLiNER2 model = GLiNER2.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
| { | |
| "source_model": "fastino/gliner2.5-small-v1", | |
| "source_revision": "7e6f537f10337497069276892a5ef435028252ce", | |
| "package": "build/gliner2_small_classification_fp16_L128_K8.mlpackage", | |
| "package_bytes": 151542752, | |
| "native_total_parameters": 73881879, | |
| "exported_parameters": 70944385, | |
| "wrapper_max_logit_error": 4.76837158203125e-07, | |
| "coremltools": "9.0", | |
| "torch": "2.7.0", | |
| "cases": [ | |
| { | |
| "text": "The rocket launched successfully.", | |
| "native_label": "science", | |
| "coreml_label": "science", | |
| "native_confidence": 0.9989821314811707, | |
| "coreml_confidence": 0.9989795088768005, | |
| "absolute_confidence_error": 2.6226043701171875e-06 | |
| }, | |
| { | |
| "text": "The team won the football championship.", | |
| "native_label": "sports", | |
| "coreml_label": "sports", | |
| "native_confidence": 0.9999417066574097, | |
| "coreml_confidence": 0.9999417066574097, | |
| "absolute_confidence_error": 0.0 | |
| }, | |
| { | |
| "text": "The budget was approved by parliament.", | |
| "native_label": "politics", | |
| "coreml_label": "politics", | |
| "native_confidence": 0.9999653100967407, | |
| "coreml_confidence": 0.9999654293060303, | |
| "absolute_confidence_error": 1.1920928955078125e-07 | |
| } | |
| ] | |
| } | |