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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>OctoPack: Instruction Tuning Code Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2308.07124/</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/2308.07124/feed.xml" rel="self" type="application/rss+xml" /><item><title>OctoPack: Instruction Tuning Code Large Language Models — HN submission</title><link>https://news.ycombinator.com/item?id=37158509</link><guid isPermaLink="false">urn:hackerpapers:submission:2308.07124:37158509</guid><pubDate>Thu, 17 Aug 2023 07:51:25 GMT</pubDate><description>&lt;p&gt;OctoPack: Instruction Tuning Code Large Language Models&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2308.07124/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>OctoPack: Instruction Tuning Code Large Language Models — mentioned by wsxiaoys</title><link>https://news.ycombinator.com/item?id=37143479</link><guid isPermaLink="false">urn:hackerpapers:mention:2308.07124:37143479</guid><pubDate>Wed, 16 Aug 2023 06:26:18 GMT</pubDate><description>&lt;p&gt;Paper: https://arxiv.org/abs/2308.07124 Highlights: This paper demonstrates the instruct fine-tuning code for Language Model Models (LLMs) using public Github commit data. The proposed method achieves the highest HumanEval pass@1 accuracy among permissive licensed LLM models.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2308.07124/"&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>
