🌟 BART
# 🌟New model addition

## Model description

method for pre-training seq2seq models by de-noising text. BART outperforms previous work on a bunch of generation tasks (summarization/dialogue/QA), while getting similar performance to RoBERTa on SQuAD/GLUE

[BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://arxiv.org/pdf/1910.13461.pdf)

Amazing results on text summarization.

## Open Source status

* [x] the model implementation is available: not yet
* [x] the model weights are available: not yet
* [ ] who are the authors: @yinhanliu @ernamangoyal 
@thomwolf another encoder-decoder<|||||>Was released today: https://github.com/pytorch/fairseq/tree/master/examples/bart 🎉<|||||>Let me know if you guys plan to add xsum/eli5/cnn-dm ft with our released bart into hugging face. <|||||>Is there any news on this?<|||||>any progress on this one? also thanks :)<|||||>I'm getting started on this Feb 4!