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 GLiNER2 model = GLiNER2.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
| { | |
| "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 | |
| } | |
| ] | |
| } | |