<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>DeepSeek on akenji&#39;s lab</title>
    <link>https://akenji3.github.io/en/tags/deepseek/</link>
    <description>Recent content in DeepSeek on akenji&#39;s lab</description>
    <generator>Hugo</generator>
    <language>en</language>
    <lastBuildDate>Tue, 28 Jan 2025 00:00:00 +0000</lastBuildDate>
    <atom:link href="https://akenji3.github.io/en/tags/deepseek/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Using LLM based on DeepSeek-R1-Distill-Qwen-14B/32B with additional Japanese language training</title>
      <link>https://akenji3.github.io/en/post/20250128_deepseek-ca/</link>
      <pubDate>Tue, 28 Jan 2025 00:00:00 +0000</pubDate>
      <guid>https://akenji3.github.io/en/post/20250128_deepseek-ca/</guid>
      <description>&lt;h2 id=&#34;motivation&#34;&gt;Motivation&lt;/h2&gt;&#xA;&lt;p&gt;I have been studying PINNs and related OpenFOAM for a while, but yesterday there was a big news in LLM area and I decided to use Deep Seek-R1 which had an impact not only on LLM area but also on stock prices. Since I could not use it as it is in my environment, I used a compacted LLM with quantization.&lt;/p&gt;&#xA;&lt;p&gt;This time, I used Ollama and Open WebUI to use the quantized model from a browser, and I will summarize the contents.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
