XLM-RoBERTa

The XLM-RoBERTa model was proposed in Unsupervised Cross-lingual Representation Learning at Scale by Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer and Veselin Stoyanov. It is based on Facebook’s RoBERTa model released in 2019. It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data.

Note

This class is nearly identical to the PyTorch implementation of XLM-RoBERTa in Huggingface Transformers. For more information, visit the corresponding section in their documentation.

XLMRobertaConfig

XLMRobertaTokenizer

XLMRobertaModel

XLMRobertaModelWithHeads

XLMRobertaForMaskedLM

XLMRobertaForSequenceClassification

XLMRobertaForMultipleChoice

XLMRobertaForTokenClassification