Hi,
Yes you can take a look at the notebooks I made regarding fine-tuning T5 on custom data: Transformers-Tutorials/T5 at master · NielsRogge/Transformers-Tutorials · GitHub 8
Note that seq2seq models like T5/BART are very general: they just take a sequence as input, and produce another sequence as output. So this could be anything, e.g.

translating from one language to another (input sequence: French sentence, output sequence: English sentence for instance)
summarizing long text (input sequence: long article, output sequence: short summary)
text-to-SQL (input sequence: text describing a query in natural language, output sequence: SQL query)
code-to-docstring (this is what I do in one of the notebooks linked above)
SQL-to-text
etc.

So definitely, keywords-to-sentence will also work well.