{"id":37647,"date":"2026-01-05T16:27:10","date_gmt":"2026-01-05T15:27:10","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/anyone-struggling-to-find-high-quality-non-english-training-data\/"},"modified":"2026-01-05T16:27:10","modified_gmt":"2026-01-05T15:27:10","slug":"anyone-struggling-to-find-high-quality-non-english-training-data","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/anyone-struggling-to-find-high-quality-non-english-training-data\/","title":{"rendered":"Anyone Struggling To Find High-quality Non-English Training Data?"},"content":{"rendered":"<p><!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>Working on a few local AI use cases and hitting the same wall: lack of clean, high-quality non-English data.<\/p>\n<p>English datasets are everywhere, but once you go into local languages\/dialects, quality drops fast\u2014noisy labels, inconsistent formats, cultural gaps. Fine-tuning models for real-world local use becomes painful.<\/p>\n<p>Curious from others building outside the US\/EU bubble:<\/p>\n<ul>\n<li>Where do you usually source non-English data?<\/li>\n<li>What\u2019s the biggest issue: quantity, quality, or context?<\/li>\n<li>Have you paid for custom datasets before?<\/li>\n<\/ul>\n<p>Feels like models are getting better faster than the data feeding them.<\/p>\n<\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/Kind_Buyer8931\"> \/u\/Kind_Buyer8931 <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1q4n9w6\/anyone_struggling_to_find_highquality_nonenglish\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1q4n9w6\/anyone_struggling_to_find_highquality_nonenglish\/\">[comments]<\/a><\/span><\/p><div class='watch-action'><div class='watch-position align-right'><div class='action-like'><a class='lbg-style1 like-37647 jlk' href='javascript:void(0)' data-task='like' data-post_id='37647' data-nonce='65e0e39b87' rel='nofollow'><img class='wti-pixel' src='https:\/\/www.graviton.at\/letterswaplibrary\/wp-content\/plugins\/wti-like-post\/images\/pixel.gif' title='Like' \/><span class='lc-37647 lc'>0<\/span><\/a><\/div><\/div> <div class='status-37647 status align-right'><\/div><\/div><div class='wti-clear'><\/div>","protected":false},"excerpt":{"rendered":"<p>Working on a few local AI use cases and hitting the same wall: lack of clean, high-quality&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"class_list":["post-37647","post","type-post","status-publish","format-standard","hentry","category-datatards","wpcat-85-id"],"_links":{"self":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/37647","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/comments?post=37647"}],"version-history":[{"count":0,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/37647\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/media?parent=37647"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/categories?post=37647"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/tags?post=37647"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}