Pre-training/fine-tuning Seq2Seq model for spelling and/or grammar correction in French
Pre-training/fine-tuning Seq2Seq model for spelling and/or grammar correctionFor this project, one can use a randomly initialized or a pre-trained BART/T5 model.ModelPre-trainedBART,T5models can be found on the model hub.DatasetsThe dataset for this model can be prepared as described in thisblog post.One can make useOSCAR. The dataset is also available through thedatasetslibrary here:oscar · Datasets at Hugging Face.Available training scriptsAs this will be a Seq2Seq model, therun_summarization_flax.pyscript can be used for training.(Optional) Desired project outcomeThe desired outcome is to train a spelling correction model for the French language. This can be showcased directly on the hub or with a streamlit  or gradio app.(Optional) ChallengesImplementing the dataset noising function would be the challenging part of the project.(Optional) Links to read uponMicrosoft Research – 8 Feb 21Speller100 expands spelling correction technology to 100+ languagesResearchers in Microsoft Search and AI created Speller100 to expand spelling correction technology to 100-plus languages. Learn how it uses the concept of language families and zero-shot learning to make spelling correction more inclusive of...
2021-06-26T07:07:35Z
Hi@valhallaI have previously worked on grammar correction for English using T5, and it gives a great result. It would an exciting task to do same on French, would like to be part of this project.
2021-06-29T20:40:17Z
This one sounds interesting…
2021-06-30T08:04:53Z
Awesome! Let’s define this project thenAdded you the team@khalidsaifullaahand@Vaibhavbrkn. Let me know if you have nay comments either here or in thesheet.
2021-06-30T08:37:31Z
Thanks@valhalla, but since I have new commitment for some projects, I can no longer will be a part of this project.
2021-06-30T09:00:09Z
Noted, removed you from the team.
2021-08-11T12:41:35Z
interested in this project