Word Sense Disambiguation (WSD) with Hugging Face Models
Hi all, I would be interested in fine-tuning or training a model from Hugging Face to perform word sense disambiguation (WSD) with a dataset (dictionary) of my own. However, I am not sure how to do it. There is no much information available on how to implement WSD out there, at least other than using Lesk algorithm (nltk).I have seen that this user (jpelhaw/t5-word-sense-disambiguation · Hugging Face) managed to fine-tune the T5 model on the SemCor dataset but there is no info on how he did it.In particular, I have the following questions:Is there a particular fine-tuning procedure for this type of task?Could I use a model from Hugging Face that has not been trained to perform this task before?Any help or reference documentation is welcome. Thank you in advance!