Tensorflow XLM-RoBERTa

In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.

XLM-RoBERTa

XLM-RoBERTa 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.jsontf_model.h5
jplu/tf-xlm-roberta-large config.jsontf_model.h5

Usage

With Transformers >= 2.4 the Tensorflow models of XLM-RoBERTa can be loaded like:

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.

Acknowledgments

Thanks to all the Huggingface team for the support and their amazing library!

New

Select AutoNLP in the “Train” menu to fine-tune this model automatically.

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