Methods › Sequential › Sequence To Sequence Models › mBARTHez
mBARTHez
Introduced by Moussa Kamal Eddine et al. in BARThez: a Skilled Pretrained French Sequence-to-Sequence Model
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
BARThez is a self-supervised transfer learning model for the French language based on BART. Compared to existing BERT-based French language models such as CamemBERT and FlauBERT, BARThez is well-suited for generative tasks, since not only its encoder but also its decoder is pretrained.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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BARThez: a Skilled Pretrained French Sequence-to-Sequence Model 23 Oct 2020 · 5 repositories · arXiv:2010.12321
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| FLUE | 1 |
| Natural Language Understanding | 1 |
| OrangeSum | 1 |
| Self-Supervised Learning | 1 |
| Text Summarization | 1 |
| Transfer Learning | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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