In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
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.
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")
model = TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-large")
All models are available on the Huggingface model hub.
Thanks to all the Huggingface team for the support and their amazing library!
Select AutoNLP in the “Train” menu to fine-tune this model automatically.
- Downloads last month