🚀 Model Card for GLiNER-small
GLiNER is a Named Entity Recognition (NER) model. It can identify any entity type with a bidirectional transformer encoder (BERT-like). It offers a practical alternative to traditional NER models, which are restricted to predefined entities, and Large Language Models (LLMs). LLMs are flexible but costly and large for resource-constrained scenarios. This version is trained on the Pile-NER dataset for research purposes.
🚀 Quick Start
GLiNER provides a convenient way to perform named entity recognition. After installation, you can quickly start using it to identify entities in text.
✨ Features
- Flexible Entity Identification: Capable of identifying any entity type.
- Practical Alternative: Offers an alternative to traditional NER models and LLMs.
- Trained on Specific Dataset: Trained on the Pile-NER dataset for research.
📦 Installation
To use this model, you must install the GLiNER Python library:
!pip install gliner
💻 Usage Examples
Basic Usage
Once you've downloaded the GLiNER library, you can import the GLiNER
class. You can then load this model using GLiNER.from_pretrained
and predict entities with predict_entities
.
from gliner import GLiNER
model = GLiNER.from_pretrained("urchade/gliner_small-v1")
text = """
Cristiano Ronaldo dos Santos Aveiro (Portuguese pronunciation: [kɾiʃˈtjɐnu ʁɔˈnaldu]; born 5 February 1985) is a Portuguese professional footballer who plays as a forward for and captains both Saudi Pro League club Al Nassr and the Portugal national team. Widely regarded as one of the greatest players of all time, Ronaldo has won five Ballon d'Or awards,[note 3] a record three UEFA Men's Player of the Year Awards, and four European Golden Shoes, the most by a European player. He has won 33 trophies in his career, including seven league titles, five UEFA Champions Leagues, the UEFA European Championship and the UEFA Nations League. Ronaldo holds the records for most appearances (183), goals (140) and assists (42) in the Champions League, goals in the European Championship (14), international goals (128) and international appearances (205). He is one of the few players to have made over 1,200 professional career appearances, the most by an outfield player, and has scored over 850 official senior career goals for club and country, making him the top goalscorer of all time.
"""
labels = ["person", "award", "date", "competitions", "teams"]
entities = model.predict_entities(text, labels)
for entity in entities:
print(entity["text"], "=>", entity["label"])
Output Example
Cristiano Ronaldo dos Santos Aveiro => person
5 February 1985 => date
Al Nassr => teams
Portugal national team => teams
Ballon d'Or => award
UEFA Men's Player of the Year Awards => award
European Golden Shoes => award
UEFA Champions Leagues => competitions
UEFA European Championship => competitions
UEFA Nations League => competitions
Champions League => competitions
European Championship => competitions
📚 Documentation
Links
- Paper: https://arxiv.org/abs/2311.08526
- Repository: https://github.com/urchade/GLiNER
Available models
Named Entity Recognition benchmark result

🔧 Technical Details
The model is based on a bidirectional transformer encoder (BERT-like) for named entity recognition. It has been trained on the Pile-NER dataset for research purposes.
📄 License
The model is released under the cc-by-nc-4.0 license for most versions, and apache-2.0 for v2 and v2.1.
Model Authors
The model authors are:
Citation
@misc{zaratiana2023gliner,
title={GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer},
author={Urchade Zaratiana and Nadi Tomeh and Pierre Holat and Thierry Charnois},
year={2023},
eprint={2311.08526},
archivePrefix={arXiv},
primaryClass={cs.CL}
}