Felix
# 🌟 New model addition

## Model description

New model released by [google](https://github.com/google-research/google-research/tree/master/felix)

## Open source status

* [x] the model implementation is available: https://github.com/google-research/google-research/tree/master/felix
* [x] the model weights are available: https://github.com/google-research/google-research/tree/master/felix (pretrained `bert-base-cased` can be used)
* [x] who are the authors: @Jmallins

Can I help with this, @patrickvonplaten ?<|||||>Hey @mrm8488,

It would be amazing if you're interested in adding this model. It looks like a difficult one, but I'd definitely try to help you as much as I can if you want to add it :-)<|||||>Looking forward ! <|||||>@ArthurZucker @younesbelkada (the ML engineers currently in charge of the text models). This has been collecting dust for a while. I still think it's relevant because it's the only encoder-only model that I'm aware of that can do text editing. Encoder-only models are faster than encoder-decoder and decoder-only models for inference.<|||||>This might be of interest for @fxmarty 👀 <|||||>(I mean, I suppose LaserTagger is also encoder-only, but FELIX came later and outperforms LaserTagger in both "%exact match with the reference sentence" and latency.)<|||||>Is anyone working on this? If not, I might try to take a shot at it...but first I'd ask if anyone has implemented already anything related to this model or this remained self-contained in the issues cathegory.<|||||>I think you can take this on! <|||||>Is there any new update on this? This approach for text editing with PointerNet reordering feels like a very important step for text editing and faster text generation inference. Is text editing, in general, something the HuggingFace team is interested in pursuing?<|||||>@afonso-sousa so far I didn't have time to work on this. I will eventually find the time, I hope this soon enough, but I would do it in my free time so I have no guarantees. But I'm not jealous: if anyone finds time to do it before me please do!