Instructions to use mlboydaisuke/GLiNER2-PII-CoreAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use mlboydaisuke/GLiNER2-PII-CoreAI with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("mlboydaisuke/GLiNER2-PII-CoreAI") - Notebooks
- Google Colab
- Kaggle
Link the card back to its collection and the request box
Browse files
README.md
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- Base model: [fastino/gliner2-privacy-filter-PII-multi](https://huggingface.co/fastino/gliner2-privacy-filter-PII-multi) (Apache-2.0), on [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) (MIT).
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- Conversion + Swift-port reference: [CoreAI-Model-Zoo](https://github.com/john-rocky/CoreAI-Model-Zoo).
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- Base model: [fastino/gliner2-privacy-filter-PII-multi](https://huggingface.co/fastino/gliner2-privacy-filter-PII-multi) (Apache-2.0), on [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) (MIT).
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- Conversion + Swift-port reference: [CoreAI-Model-Zoo](https://github.com/john-rocky/CoreAI-Model-Zoo).
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---
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**More models in this format:** [Core AI Model Zoo](https://huggingface.co/collections/mlboydaisuke/core-ai-model-zoo-6a7ff330f753e8dcae04671a) — 75 models, each with the recipe that produced it.
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**Want a different model on-device?** [Open a request](https://github.com/john-rocky/on-device-requests) — free, open weights only; the export and its measured numbers get published publicly.
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