Gliner ITA LARGE

🚀 GLiNER: Token Classification Model

GLiNER is a generalist model for named entity recognition, which uses a bidirectional transformer to classify tokens.

🚀 Quick Start

To quickly get started with this model, you need to install the necessary libraries and follow the basic usage steps.

📦 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("DeepMount00/GLiNER_ITA_LARGE")

text = """..."""

labels = ["label1", "label2"]

entities = model.predict_entities(text, labels)

for entity in entities:
    print(entity["text"], "=>", entity["label"])

📚 Documentation

Model Author

• Michele Montebovi

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}
}

## 📄 License
This project is licensed under the Apache-2.0 license.