Create a spellchecking system
Please read the topic categorydescriptionto understand what this is all aboutDescriptionNowadays you can find spellchecker everywhere - on your phone, Microsoft Word, and so on. The goal of this project is to train a Transformer model to automatically correct our spelling in a language of your choosing!Model(s)You can frame spellchecking as a sequence-to-sequence task, so a good starting point is to checkout the machine translation example in Chapter 7 of theCourse. Once you understand that, a T5 or mT5 model is a good start to train your models.DatasetsTheGitHub Typo corpusis a good place to start. An alternative is to useback-translationto create your own corpus of noisy labels, since most machine translation systems typically introduce small errors this way.ChallengesThis is a rather open-ended project, and one that might require some careful data preprocessing / augmentation. A good starting strategy would be to adapt theexamplegiven in the resources below, but using theecosystem instead of thefairseqlibrary.Desired project outcomesCreate a Streamlit or Gradio app onSpacesthat [Fill description]Don’t forget to push all your models and datasets to the Hub so others can build on them!Additional resourceshttp://www.realworldnlpbook.com/blog/unreasonable-effectiveness-of-transformer-spell-checker.htmlhttps://github.com/neuspell/neuspell