<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>dartos</author><text>Sometimes you don’t want to share all your data with the largest corporations on the planet.</text><parent_chain><item><author>faangguyindia</author><text>Question is why even use these small models?&lt;p&gt;When you&amp;#x27;ve Google Flash which is lightening fast and cheap.&lt;p&gt;My brother implemented it in option-k : &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;zerocorebeta&amp;#x2F;Option-K&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;zerocorebeta&amp;#x2F;Option-K&lt;/a&gt;&lt;p&gt;It&amp;#x27;s near instant.  So why waste time on small models? It&amp;#x27;s going to cost more than Google flash.</text></item><item><author>sippeangelo</author><text>For as much as I would love for this to work, I&amp;#x27;m not getting great results trying out the 1.5b model in their example notebook on Colab.&lt;p&gt;It is impressively fast, but testing it on an arxiv.org page (specifically &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;abs&amp;#x2F;2306.03872&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;abs&amp;#x2F;2306.03872&lt;/a&gt;) only gives me a short markdown file containing the abstract, the &amp;quot;View PDF&amp;quot; link and the submission history. It completely leaves out the title (!), authors and other links, which are definitely present in the HTML in multiple places!&lt;p&gt;I&amp;#x27;d argue that Arxiv.org is a reasonable example in the age of webapps, so what gives?</text></item></parent_chain></comment><story><title>Reader-LM: Small Language Models for Cleaning and Converting HTML to Markdown</title><url>https://jina.ai/news/reader-lm-small-language-models-for-cleaning-and-converting-html-to-markdown/?nocache=1</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>oezi</author><text>What is Google Flash? Do you mean Gemini Flash? If so, then the article talks about that general purpose LLMs are worse than this specialized LLM for Markdown conversion.</text><parent_chain><item><author>faangguyindia</author><text>Question is why even use these small models?&lt;p&gt;When you&amp;#x27;ve Google Flash which is lightening fast and cheap.&lt;p&gt;My brother implemented it in option-k : &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;zerocorebeta&amp;#x2F;Option-K&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;zerocorebeta&amp;#x2F;Option-K&lt;/a&gt;&lt;p&gt;It&amp;#x27;s near instant.  So why waste time on small models? It&amp;#x27;s going to cost more than Google flash.</text></item><item><author>sippeangelo</author><text>For as much as I would love for this to work, I&amp;#x27;m not getting great results trying out the 1.5b model in their example notebook on Colab.&lt;p&gt;It is impressively fast, but testing it on an arxiv.org page (specifically &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;abs&amp;#x2F;2306.03872&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;abs&amp;#x2F;2306.03872&lt;/a&gt;) only gives me a short markdown file containing the abstract, the &amp;quot;View PDF&amp;quot; link and the submission history. It completely leaves out the title (!), authors and other links, which are definitely present in the HTML in multiple places!&lt;p&gt;I&amp;#x27;d argue that Arxiv.org is a reasonable example in the age of webapps, so what gives?</text></item></parent_chain></comment><story><title>Reader-LM: Small Language Models for Cleaning and Converting HTML to Markdown</title><url>https://jina.ai/news/reader-lm-small-language-models-for-cleaning-and-converting-html-to-markdown/?nocache=1</url></story>