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    <title>Llama-Cpp-Python on akenji&#39;s lab</title>
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    <description>Recent content in Llama-Cpp-Python on akenji&#39;s lab</description>
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      <title>llama-cpp-python - impact of numpy version upgrade</title>
      <link>https://akenji3.github.io/en/post/20240704_numpy_v2/</link>
      <pubDate>Thu, 04 Jul 2024 00:00:00 +0000</pubDate>
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      <description>&lt;h2 id=&#34;introduction&#34;&gt;Introduction.&lt;/h2&gt;&#xA;&lt;p&gt;&lt;a href=&#34;https://github.com/numpy/numpy/releases&#34;&gt;NumPy 2.0.0&lt;/a&gt; was released on June 16. I first noticed it the other day when I tried RAG with using langchain and got an error when building the docker container. Later, I encountered another error in CMake when trying to incorporate llama-cpp-python.&lt;/p&gt;&#xA;&lt;p&gt;This article summarizes my responses to the two errors I recently experienced.&lt;/p&gt;&#xA;&lt;h2 id=&#34;dealing-with-errors-related-to-numpy-200&#34;&gt;Dealing with errors related to NumPy 2.0.0&lt;/h2&gt;&#xA;&lt;h4 id=&#34;background&#34;&gt;Background&lt;/h4&gt;&#xA;&lt;p&gt;I recently decided to learn RAG properly, I purchased a japanese book called &lt;a href=&#34;https://www.amazon.co.jp/dp/427423195X&#34;&gt;LLM fine tuning and RAG&lt;/a&gt;. The book uses langchain, so I decided to create a docker container for jupyterlab that incorporates the langchain library.&lt;/p&gt;</description>
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      <title>Try the Chatbot UI</title>
      <link>https://akenji3.github.io/en/post/20240506_llamaserver/</link>
      <pubDate>Mon, 06 May 2024 00:00:00 +0000</pubDate>
      <guid>https://akenji3.github.io/en/post/20240506_llamaserver/</guid>
      <description>&lt;h2 id=&#34;introduction&#34;&gt;Introduction&lt;/h2&gt;&#xA;&lt;p&gt;In &lt;a href=&#34;https://akenji3.github.io/en/post/20240503_llama-cpp-python/&#34;&gt;a recent post&lt;/a&gt;, I ran the ELYZA 7B model in a local environment using llama-cpp-python. In that post, I mentioned that &amp;ldquo;about the future&amp;rdquo; I would like to try to build a system that can chat like ChatGPT.&lt;/p&gt;&#xA;&lt;p&gt;This time, I built a system that can chat like ChatGPT on a docker container, and I summarize its contents here.&lt;/p&gt;</description>
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      <title>Running Elyza models on GPU using llama-cpp-python</title>
      <link>https://akenji3.github.io/en/post/20240503_llama-cpp-python/</link>
      <pubDate>Fri, 03 May 2024 00:00:00 +0000</pubDate>
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      <description>&lt;h2 id=&#34;motivation&#34;&gt;Motivation&lt;/h2&gt;&#xA;&lt;p&gt;Quantization is essential to run LLM on the local workstation (12-16 GB of GPU memory). In this post, I summarize my attempt to maximize GPU resources using llama-cpp-python.&lt;/p&gt;&#xA;&lt;p&gt;The content includes some of my mistakes, as I got into some areas due to my lack of understanding.&lt;/p&gt;</description>
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