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 GLiNER2 model = GLiNER2.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
| { | |
| "source_model": "fastino/gliner2.5-multi-v1", | |
| "source_revision": "a221b77a8baf4a613b8f8652661d41fa10a5641e", | |
| "package": "build/gliner2_multi_classification_fp32_L128_K8.mlpackage", | |
| "package_bytes": 1152027886, | |
| "native_total_parameters": 287355159, | |
| "exported_parameters": 278719489, | |
| "wrapper_max_logit_error": 0.0, | |
| "coremltools": "9.0", | |
| "torch": "2.7.0", | |
| "cases": [ | |
| { | |
| "text": "The rocket launched successfully.", | |
| "native_label": "sports", | |
| "coreml_label": "sports", | |
| "native_confidence": 0.5060790777206421, | |
| "coreml_confidence": 0.5060756206512451, | |
| "absolute_confidence_error": 3.4570693969726562e-06 | |
| }, | |
| { | |
| "text": "The team won the football championship.", | |
| "native_label": "sports", | |
| "coreml_label": "sports", | |
| "native_confidence": 0.9999996423721313, | |
| "coreml_confidence": 0.9999996423721313, | |
| "absolute_confidence_error": 0.0 | |
| }, | |
| { | |
| "text": "The budget was approved by parliament.", | |
| "native_label": "politics", | |
| "coreml_label": "politics", | |
| "native_confidence": 0.9999977350234985, | |
| "coreml_confidence": 0.9999977350234985, | |
| "absolute_confidence_error": 0.0 | |
| } | |
| ] | |
| } | |