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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Gemma 2: Improving Open Language Models at a Practical Size · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2408.00118/</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/2408.00118/feed.xml" rel="self" type="application/rss+xml" /><item><title>Gemma 2: Improving Open Language Models at a Practical Size — mentioned by tucnak</title><link>https://news.ycombinator.com/item?id=41846153</link><guid isPermaLink="false">urn:hackerpapers:mention:2408.00118:41846153</guid><pubDate>Tue, 15 Oct 2024 08:12:00 GMT</pubDate><description>&lt;p&gt;The LIMA paper, I think, would be a good place to start https://arxiv.org/abs/2305.11206 You can create inputs for DPO/ORPO synthetically which is a huge one as previously it would require gigantic investments https://arxiv.org/abs/2402.10379 There&amp;#x27;s also the gemma2 paper has advanced SOTA in distil; on a side-note, there&amp;#x27;s many reasons for it but vocab_size and good sizes 9b/27b, IMHO it&amp;#x27;s currently the best model for i.e. Ukrainian. in fact, I prefer it to anything else there&amp;#x27;s, including the much larger llama&amp;#x27;s—by a mile! The model is a triumph of synthetic datasets.…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2408.00118/"&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>
