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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>An empirical study of LLaMA3 quantization: from LLMs to MLLMs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2404.14047/</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/2404.14047/feed.xml" rel="self" type="application/rss+xml" /><item><title>An empirical study of LLaMA3 quantization: from LLMs to MLLMs — mentioned by sbierwagen</title><link>https://news.ycombinator.com/item?id=40292542</link><guid isPermaLink="false">urn:hackerpapers:mention:2404.14047:40292542</guid><pubDate>Tue, 07 May 2024 23:05:05 GMT</pubDate><description>&lt;p&gt;Interestingly enough, Llama3 suffers more performance loss than Llama2 did at identical quantizations. https://arxiv.org/abs/2404.14047 There&amp;#x27;s some speculation that a net trained for more epochs on more data learns to pack more information into the weights, and so does worse when weight data is degraded.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2404.14047/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
