GLiNER2
Safetensors
extractor
Token Classification
Zero-Shot Classification
Text Classification
relation extraction
Structured extraction
Instructions to use fastino/gliner2-multi-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use fastino/gliner2-multi-v1 with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("fastino/gliner2-multi-v1") # 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
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# GLiNER2: Unified Schema-Based Information Extraction and Text Classification
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> *Extract entities, classify text, parse structured data, and extract relations—all in one efficient model.*
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<a href="https://pioneer.ai?utm_source=huggingface" target="_blank" rel="noreferrer" style="text-decoration:none;">
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<img src="https://img.shields.io/badge/Deploy-GLiNER2-EA4335" alt="Fine-tune and Deploy GLiNER2 with Pioneer" style="vertical-align:middle;">
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</a> <a href="https://arxiv.org/abs/2507.18546" target="_blank" rel="noreferrer" style="text-decoration:none;">
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<img src="https://img.shields.io/badge/arXiv-2605.07982-b31b1b.svg?logo=arxiv" alt="arXiv Paper" style="vertical-align:middle;">
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<a href="https://github.com/fastino-ai/GLiNER2" target="_blank" rel="noreferrer" style="text-decoration:none;">
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<img src="https://img.shields.io/badge/GitHub-GLiNER2-black?logo=github" alt="GitHub" style="vertical-align:middle;">
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<a href="https://x.com/fastinoAI" target="_blank" rel="noreferrer" style="text-decoration:none;">
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<img src="https://img.shields.io/twitter/follow/:fastinoAI" alt="Follow @fastinoAI" style="vertical-align:middle;">
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# GLiNER2: Unified Schema-Based Information Extraction and Text Classification
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> *Extract entities, classify text, parse structured data, and extract relations—all in one efficient model.*
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