Token Classification
GLiNER
English
named-entity-recognition
data-mention-extraction
survey-detection
geocoded-data
DHS
census
ml-intern
Instructions to use rafmacalaba/gliner-large-data-mentions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use rafmacalaba/gliner-large-data-mentions with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("rafmacalaba/gliner-large-data-mentions") - Notebooks
- Google Colab
- Kaggle
Update ML Intern artifact metadata
Browse files
README.md
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- geocoded-data
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- DHS
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- census
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library_name: gliner
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base_model: urchade/gliner_large-v2.1
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---
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- Dataset mention extraction: [arxiv:2502.10263](https://arxiv.org/abs/2502.10263) (World Bank, 2025)
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- GSAP-NER (scholarly entity extraction): [arxiv:2311.09860](https://arxiv.org/abs/2311.09860)
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- Coleridge "Show US the Data" Kaggle: best public dataset for dataset mentions in social science papers
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- geocoded-data
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- DHS
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- census
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- ml-intern
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library_name: gliner
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base_model: urchade/gliner_large-v2.1
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---
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- Dataset mention extraction: [arxiv:2502.10263](https://arxiv.org/abs/2502.10263) (World Bank, 2025)
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- GSAP-NER (scholarly entity extraction): [arxiv:2311.09860](https://arxiv.org/abs/2311.09860)
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- Coleridge "Show US the Data" Kaggle: best public dataset for dataset mentions in social science papers
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<!-- ml-intern-provenance -->
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## Generated by ML Intern
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This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
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- Try ML Intern: https://smolagents-ml-intern.hf.space
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- Source code: https://github.com/huggingface/ml-intern
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