Bert Base En Es Cased

🚀 bert-base-en-es-cased

We are sharing smaller versions of bert-base-multilingual-cased that handle a custom number of languages. These versions preserve the original accuracy by producing the same representations as the original model, unlike distilbert-base-multilingual-cased.

🚀 Quick Start

We are sharing smaller versions of bert-base-multilingual-cased that can handle a specific number of languages. Different from distilbert-base-multilingual-cased, our versions generate exactly the same representations as the original model, thus maintaining the original accuracy.

For more information, please refer to our paper: Load What You Need: Smaller Versions of Multilingual BERT.

✨ Features

• Share smaller versions of multilingual BERT models.
• Preserve the original accuracy by generating the same representations as the original model.

📦 Installation

No specific installation steps are provided in the original text.

💻 Usage Examples

Basic Usage

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-es-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-en-es-cased")

To generate other smaller versions of multilingual transformers, please visit our Github repo.

How to cite

@inproceedings{smallermbert,
  title={Load What You Need: Smaller Versions of Mutlilingual BERT},
  author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire},
  booktitle={SustaiNLP / EMNLP},
  year={2020}
}

📚 Documentation

Model Information

Widget Examples

• "Google generated 46 billion [MASK] in revenue."
• "Paris is the capital of [MASK]."
• "Algiers is the largest city in [MASK]."

📄 License

This project is licensed under the Apache-2.0 license.

Contact

Please contact amine@geotrend.fr for any questions, feedback, or requests.