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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2402.00159/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2402.00159/feed.xml" rel="self" type="application/rss+xml" /><item><title>Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research — mentioned by Eisenstein</title><link>https://news.ycombinator.com/item?id=46104836</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.00159:46104836</guid><pubDate>Mon, 01 Dec 2025 08:20:17 GMT</pubDate><description>&lt;p&gt;&amp;gt; How many models are only trained on legal[0] data? None, since &amp;#x27;legal&amp;#x27; for AI training is not yet defined, but Olma is trained on the Dolma 3 dataset, which is 1. Common crawl 2. Github 3. Wikipedia, Wikibooks 4. Reddit (pre-2023) 5. Semantic Scholar 6. Project Gutenberg * https://arxiv.org/pdf/2402.00159&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.00159/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research — mentioned by strangecasts</title><link>https://news.ycombinator.com/item?id=44031240</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.00159:44031240</guid><pubDate>Mon, 19 May 2025 16:01:14 GMT</pubDate><description>&lt;p&gt;Obviously I can only speculate since I neither have access to their dataset nor interest in paying for API access, but crawling and dataset cleaning have gotten much better since the GPT-2 days, especially after Microsoft&amp;#x27;s PHI models [1] demonstrated how much dataset construction matters for parameter efficiency and toxicity. Having some basic content filtering is a pretty established part of data cleanup -- e.g. the fastText toxicity classifiers in the Dolma pipeline [2] -- which obviously still leaves in bad data, but certainly won&amp;#x27;t leave in the entirety of /b/ If shoddy data collection…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.00159/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research — mentioned by benreesman</title><link>https://news.ycombinator.com/item?id=40694666</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.00159:40694666</guid><pubDate>Sun, 16 Jun 2024 04:21:46 GMT</pubDate><description>&lt;p&gt;https://arxiv.org/pdf/2402.00159 MIT, the Steel Factory, Cal, UDub and what, 37 authors pushed a preprint and no one heard about it? @dang I can’t be the only one who has had it on this GPT-5 test flight shit. I don’t care how many clean Azure IPv4 blocks Altman has, throw this motherfucker out.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.00159/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research — mentioned by dwagnerkc</title><link>https://news.ycombinator.com/item?id=39228194</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.00159:39228194</guid><pubDate>Fri, 02 Feb 2024 13:19:16 GMT</pubDate><description>&lt;p&gt;That post also very helpfully links to another paper they published alongside the OLMo paper just on the dataset. Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research https://arxiv.org/abs/2402.00159&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.00159/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
