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Open Source Model Profile · microsoft

infoxlm-base

infoxlm-base is a microsoft XLM-RoBERTa fill-mask model. According to the model card, it is linked to the InfoXLM NAACL 2021 cross-lingual pre-training work.

Publisher
microsoft
Task
fill-mask
Model type
xlm-roberta
License
Unknown
Library
transformers
Publication status
Accepted · not indexed

Model overview

infoxlm-base is published by microsoft as a fill-mask model. The captured configuration identifies XLMRobertaForMaskedLM with model type xlm-roberta. According to the model card, it is presented as InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training (NAACL 2021).

Recorded capabilities

Masked-LM architecture

The captured configuration identifies XLMRobertaForMaskedLM with model type xlm-roberta.

Documented InfoXLM lineage

According to the model card, the release is presented as InfoXLM, with the NAACL 2021 paper reference and BibTeX retained in the card.

Transformers fill-mask stack

Hub records list the fill-mask pipeline with the transformers library and xlm-roberta tags.

Use cases in the source record

  • Fill-mask masked-token workflows using the captured XLM-RoBERTa masked-LM configuration.
  • Cross-lingual pre-training research referencing the InfoXLM paper context the model card documents.

Limitations and unknowns

  • No parameter count was extracted from this record.
  • No license value was extracted from this record.
  • No evaluation results were extracted from this record.
  • No context-window value was extracted from this record.
  • Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: microsoft/infoxlm-base

Captured: Unknown. Processed: 2026-09-07T19:34:51.959633+00:00.

InfoXLM InfoXLM (NAACL 2021, paper , repo , model ) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training. MD5 b9d214025837250ede2f69c9385f812c config.json bd6b1f392293f0cd9cd829c02971ecd9 pytorch_model.bin bf25eb5120ad92ef5c7d8596b5dc4046 sentencepiece.bpe.model eedbd60a7268b9fc45981b849664f747 tokenizer.json BibTeX @inproceedings{chi-etal-2021-infoxlm, title = "{I}nfo{XLM}: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training", author={Chi, Zewen and Dong, Li and Wei, Furu and Yang, Nan and Singhal, Saksham and Wang, Wenhui and Song, Xia and Mao, Xian-Ling and Huang,…

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