---
language: th

datasets: wikipedia

license: apache-2.0
---

# bert-base-th-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-uk-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-fr-zh-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-zh-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-zh-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-pt-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-zh-hi-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: no

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-no-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-no-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-no-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-ro-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-tr-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: pl

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-pl-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-pl-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-pl-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-sw-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-pt-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-ro-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-zh-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-fr-lt-no-pl-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-lt-no-pl-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-lt-no-pl-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: lt

datasets: wikipedia

license: apache-2.0
---

# bert-base-lt-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: tr

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-tr-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-tr-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-tr-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-es-zh-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: es

datasets: wikipedia

license: apache-2.0
---

# bert-base-es-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
- text: "تقع سويسرا في [MASK] أوروبا"
- text: "إسمي محمد وأسكن في [MASK]."
---

# bert-base-en-ar-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-zh-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-fr-zh-ja-vi-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-fr-zh-ja-vi-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-en-fr-zh-ja-vi-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-pl-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: nl

datasets: wikipedia

license: apache-2.0
---

# bert-base-nl-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: zh

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-zh-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-zh-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-zh-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-fr-de-no-da-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-fr-de-no-da-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-en-fr-de-no-da-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-fr-de-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-hi-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: lt

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-lt-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-lt-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-lt-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: uk

datasets: wikipedia

license: apache-2.0
---

# bert-base-uk-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: fr

datasets: wikipedia

license: apache-2.0

widget:
- text: "Paris est la [MASK] de la France."
- text: "Paris est la capitale de la [MASK]."
- text: "L'élection américaine a eu [MASK] en novembre 2020."
---

# bert-base-fr-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: hi

datasets: wikipedia

license: apache-2.0
---

# bert-base-hi-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-ja-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-fr-zh-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-ru-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-no-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-no-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-no-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: bg

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-bg-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-bg-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-bg-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-fr-es-pt-it-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-es-pt-it-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-es-pt-it-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-es-it-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: pt

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-pt-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-pt-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-pt-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-no-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-no-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-en-no-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: vi

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-vi-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-vi-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-vi-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: da

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-da-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-da-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-da-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
- text: "Paris est la [MASK] de la France."
- text: "Paris est la capitale de la [MASK]."
- text: "L'élection américaine a eu [MASK] en novembre 2020."
- text: "تقع سويسرا في [MASK] أوروبا"
- text: "إسمي محمد وأسكن في [MASK]."
---

# bert-base-10lang-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

This model handles the following languages: english, french, spanish, german, chinese, arabic, russian, portuguese, italian, and urdu. It produces the same representations as [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) while being 22.5% smaller in size.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-10lang-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-10lang-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: en

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-el-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-fr-es-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: ro

datasets: wikipedia

license: apache-2.0
---

# bert-base-ro-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: tr

datasets: wikipedia

license: apache-2.0
---

# bert-base-tr-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: ur

datasets: wikipedia

license: apache-2.0
---

# bert-base-ur-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-es-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
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](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-sw-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-ru-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-hi-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: hi

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-hi-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-hi-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-hi-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: ro

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-ro-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ro-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-ro-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-ja-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-fr-ar-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-fr-ar-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-fr-ar-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-de-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-tr-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-lt-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: ur

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-ur-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ur-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-ur-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-zh-hi-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-en-zh-hi-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-en-zh-hi-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# bert-base-en-fr-es-de-zh-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-it-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
- text: "Paris est la [MASK] de la France."
- text: "Paris est la capitale de la [MASK]."
- text: "L'élection américaine a eu [MASK] en novembre 2020."
- text: "تقع سويسرا في [MASK] أوروبا"
- text: "إسمي محمد وأسكن في [MASK]."
---

# bert-base-15lang-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

The measurements below have been computed on a [Google Cloud n1-standard-1 machine (1 vCPU, 3.75 GB)](https://cloud.google.com/compute/docs/machine-types\#n1_machine_type):

|             Model               | Num parameters |   Size   |  Memory  | Loading time |
| ------------------------------- | -------------- | -------- | -------- | ------------ |
| bert-base-multilingual-cased    |   178 million  |  714 MB  | 1400 MB  |    4.2 sec   |
| Geotrend/bert-base-15lang-cased |   141 million  |  564 MB  | 1098 MB  |    3.1 sec   |

Handled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur and sw.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-15lang-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-15lang-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: el

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-el-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-el-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-el-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0

widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---

# bert-base-en-ur-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: fr

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-fr-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-fr-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-fr-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: multilingual

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-en-uk-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: ja

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-ja-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ja-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-ja-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: it

datasets: wikipedia

license: apache-2.0
---

# bert-base-it-cased

We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.

Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

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

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

```bibtex
@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}
}
```

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.


---
language: ar

datasets: wikipedia

license: apache-2.0
---

# distilbert-base-ar-cased

We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.

Our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).

## How to use

```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/distilbert-base-ar-cased")
model = AutoModel.from_pretrained("Geotrend/distilbert-base-ar-cased")

```

To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).

### How to cite

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

## Contact

Please contact amine@geotrend.fr for any question, feedback or request.