Gliner Large V2

🚀 Model Card for GLiNER-large-v2

GLiNER is a Named Entity Recognition (NER) model. It can identify any entity type using 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 has been trained on the NuNER dataset (commercially permissive).

🚀 Quick Start

GLiNER is a powerful tool for named entity recognition. With its unique architecture, it can handle various entity types efficiently.

✨ Features

• Capable of identifying any entity type with a bidirectional transformer encoder.
• A practical alternative to traditional NER models and LLMs.
• Trained on the commercially permissive NuNER dataset.

📦 Installation

To use this model, you must install the GLiNER Python library:

!pip install gliner

💻 Usage Examples

Basic Usage

from gliner import GLiNER

model = GLiNER.from_pretrained("urchade/gliner_largev2")

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"])

Advanced Usage

The basic usage already demonstrates the core functionality of the model. You can further customize the labels list according to your specific needs to identify different types of entities.

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 uses a bidirectional transformer encoder (BERT-like) for named entity recognition. It has been trained on the NuNER dataset, which allows it to handle various entity types.

📄 License

The model is licensed under the Apache 2.0 license.

Model Authors

The model authors are:

• Urchade Zaratiana
• Nadi Tomeh
• Pierre Holat
• Thierry Charnois