[model_cards] Migrate cards from this repo to model repos on huggingface.co (#9013)

* rm all model cards

* Update the .rst

@sgugger it is still not super crystal clear/streamlined so let me know if any ideas to make it simpler

* Add a rootlevel README.md with simple instructions/context

* Update docs/source/model_sharing.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* make style

* rm all model cards
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

model_cards/Geotrend/bert-base-en-es-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-en-fr-cased/README.md

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

model_cards/Geotrend/bert-base-en-hi-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-en-ru-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-en-sw-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-en-th-cased/README.md

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

model_cards/Geotrend/bert-base-en-tr-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-en-ur-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-en-vi-cased/README.md

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

model_cards/Geotrend/bert-base-en-zh-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-es-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-fr-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-hi-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-ru-cased/README.md

----
-language: ru
-
-datasets: wikipedia
-
-license: apache-2.0
----
-
-# bert-base-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-ru-cased")
-model = AutoModel.from_pretrained("Geotrend/bert-base-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.

model_cards/Geotrend/bert-base-sw-cased/README.md

----
-language: sw
-
-datasets: wikipedia
-
-license: apache-2.0
----
-
-# bert-base-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-sw-cased")
-model = AutoModel.from_pretrained("Geotrend/bert-base-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.

model_cards/Geotrend/bert-base-th-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-tr-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-ur-cased/README.md

----
-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.

model_cards/Geotrend/bert-base-vi-cased/README.md

----
-language: vi
-
-datasets: wikipedia
-
-license: apache-2.0
----
-
-# bert-base-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-vi-cased")
-model = AutoModel.from_pretrained("Geotrend/bert-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{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.

model_cards/Geotrend/bert-base-zh-cased/README.md

----
-language: zh
-
-datasets: wikipedia
-
-license: apache-2.0
----
-
-# bert-base-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-zh-cased")
-model = AutoModel.from_pretrained("Geotrend/bert-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{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.