Text Classification
Core ML
GLiNER2
coremltools
extractor
apple-silicon
classification
decision-model
Instructions to use FluidInference/gliner2-5-decide-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use FluidInference/gliner2-5-decide-coreml with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("FluidInference/gliner2-5-decide-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
Commit History
23 days ago
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Add `decision-model` tag
Verified signatureThis PR adds the `decision-model` tag to the model card metadata so the model shows up under the [decision-model](https://huggingface.co/models?other=decision-model) filter on the Hub.0fd8a3b
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Add L128_H4_K32 conversion report
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Add w8 L128_H4_K32 (128 tokens, 32 labels)
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Add fp16 L128_H4_K32 (128 tokens, 32 labels)
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GLiNER2.5-Decide Core ML: fp16/W8/LUT6 at L128, L256, L512 (mobius 01e6e6a)
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initial commit
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