Yor\\`ub\\'a is a widely spoken West African language with a writing system\nrich in orthographic and tonal diacritics. They provide morphological\ninformation, are crucial for lexical disambiguation, pronunciation and are\nvital for any computational Speech or Natural Language Processing tasks.\nHowever diacritic marks are commonly excluded from electronic texts due to\nlimited device and application support as well as general education on proper\nusage. We report on recent efforts at dataset cultivation. By aggregating and\nimproving disparate texts from the web and various personal libraries, we were\nable to significantly grow our clean Yor\\`ub\\'a dataset from a majority\nBibilical text corpora with three sources to millions of tokens from over a\ndozen sources. We evaluate updated diacritic restoration models on a new,\ngeneral purpose, public-domain Yor\\`ub\\'a evaluation dataset of modern\njournalistic news text, selected to be multi-purpose and reflecting\ncontemporary usage. All pre-trained models, datasets and source-code have been\nreleased as an open-source project to advance efforts on Yor\\`ub\\'a language\ntechnology.\n