Add READMEs to Tensorflow versions of CamemBERT and XLM-RoBERTa

model_cards/jplu/tf-camembert-base/README.md

@@ -0,0 +1,31 @@
+# Tensorflow CamemBERT
+
+In this repository you will find different versions of the CamemBERT model for Tensorflow.
+
+## CamemBERT
+
+[CamemBERT](https://camembert-model.fr/) is a state-of-the-art language model for French based on the RoBERTa architecture pretrained on the French subcorpus of the newly available multilingual corpus OSCAR.
+
+## Model Weights
+
+| Model                            | Downloads
+| -------------------------------- | ---------------------------------------------------------------------------------------------------------------
+| `jplu/tf-camembert-base`   | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-camembert-base/config.json) • [`tf_model.h5`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-camembert-base/tf_model.h5)
+
+## Usage
+
+With Transformers >= 2.4 the Tensorflow models of CamemBERT can be loaded like:
+
+```python
+from transformers import TFCamembertModel
+
+model = TFCamembertModel.from_pretrained("jplu/tf-camembert-base")
+```
+
+## Huggingface model hub
+
+All models are available on the [Huggingface model hub](https://huggingface.co/jplu).
+
+## Acknowledgments
+
+Thanks to all the Huggingface team for the support and their amazing library!

model_cards/jplu/tf-xlm-roberta-base/README.md

@@ -0,0 +1,36 @@
+# Tensorflow XLM-RoBERTa
+
+In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
+
+## XLM-RoBERTa
+
+[XLM-RoBERTa](https://ai.facebook.com/blog/-xlm-r-state-of-the-art-cross-lingual-understanding-through-self-supervision/) is a scaled cross lingual sentence encoder. It is trained on 2.5T of data across 100 languages data filtered from Common Crawl. XLM-R achieves state-of-the-arts results on multiple cross lingual benchmarks.
+
+## Model Weights
+
+| Model                            | Downloads
+| -------------------------------- | ---------------------------------------------------------------------------------------------------------------
+| `jplu/tf-xlm-roberta-base`   | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-base/config.json) • [`tf_model.h5`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-base/tf_model.h5)
+| `jplu/tf-xlm-roberta-large`   | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-large/config.json) • [`tf_model.h5`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-large/tf_model.h5)
+
+## Usage
+
+With Transformers >= 2.4 the Tensorflow models of XLM-RoBERTa can be loaded like:
+
+```python
+from transformers import TFXLMRobertaModel
+
+model = TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-base")
+```
+Or
+```
+model = TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-large")
+```
+
+## Huggingface model hub
+
+All models are available on the [Huggingface model hub](https://huggingface.co/jplu).
+
+## Acknowledgments
+
+Thanks to all the Huggingface team for the support and their amazing library!

model_cards/jplu/tf-xlm-roberta-large/README.md

@@ -0,0 +1,36 @@
+# Tensorflow XLM-RoBERTa
+
+In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
+
+## XLM-RoBERTa
+
+[XLM-RoBERTa](https://ai.facebook.com/blog/-xlm-r-state-of-the-art-cross-lingual-understanding-through-self-supervision/) is a scaled cross lingual sentence encoder. It is trained on 2.5T of data across 100 languages data filtered from Common Crawl. XLM-R achieves state-of-the-arts results on multiple cross lingual benchmarks.
+
+## Model Weights
+
+| Model                            | Downloads
+| -------------------------------- | ---------------------------------------------------------------------------------------------------------------
+| `jplu/tf-xlm-roberta-base`   | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-base/config.json) • [`tf_model.h5`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-base/tf_model.h5)
+| `jplu/tf-xlm-roberta-large`   | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-large/config.json) • [`tf_model.h5`](https://s3.amazonaws.com/models.huggingface.co/bert/jplu/tf-xlm-roberta-large/tf_model.h5)
+
+## Usage
+
+With Transformers >= 2.4 the Tensorflow models of XLM-RoBERTa can be loaded like:
+
+```python
+from transformers import TFXLMRobertaModel
+
+model = TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-base")
+```
+Or
+```
+model = TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-large")
+```
+
+## Huggingface model hub
+
+All models are available on the [Huggingface model hub](https://huggingface.co/jplu).
+
+## Acknowledgments
+
+Thanks to all the Huggingface team for the support and their amazing library!