roberta-base and xlm-roberta-base are both fill-mask models. See each entry for specifics.
RoBERTa base from Facebook AI, trained with the same architecture as BERT base but significantly more data, longer training schedules, larger batch sizes, and dynamic masking. Pre-trained on BookCorpus, Wikipedia, CC-News, OpenWebText, and Stories — substantially more data than the original BERT. MIT licensed with multi-framework support.
XLM-RoBERTa base from Facebook AI, pre-trained on 2.5TB of filtered CommonCrawl text across 100 languages using the RoBERTa training procedure. Enables cross-lingual transfer — models fine-tuned on labeled English data can infer on other languages without parallel annotations. The standard starting point for multilingual classification and token-level tasks.
Pick based on your compute budget and specific task requirements.