<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <title>PyPI recent updates for economize</title>
    <link>https://pypi.org/project/economize/</link>
    <description>Recent updates to the Python Package Index for economize</description>
    <language>en</language>    <item>
      <title>0.4.0</title>
      <link>https://pypi.org/project/economize/0.4.0/</link>
      <description>Composable efficiency techniques (speculative decoding, early exit, quantization, pruning, KV-cache compression, ...) for Hugging Face causal LMs.</description>
<author>f.laitenberger@gmail.com</author>      <pubDate>Wed, 04 Nov 2026 19:16:18 GMT</pubDate>
    </item>    <item>
      <title>0.3.2</title>
      <link>https://pypi.org/project/economize/0.3.2/</link>
      <description>Composable efficiency techniques (cross-layer jump drafting, early exit, speculative decoding, ...) for Hugging Face causal LMs.</description>
<author>f.laitenberger@gmail.com</author>      <pubDate>Sun, 11 Oct 2026 18:52:11 GMT</pubDate>
    </item>    <item>
      <title>0.3.1</title>
      <link>https://pypi.org/project/economize/0.3.1/</link>
      <description>Composable efficiency techniques (cross-layer jump drafting, early exit, speculative decoding, ...) for Hugging Face causal LMs.</description>
<author>f.laitenberger@gmail.com</author>      <pubDate>Sun, 11 Oct 2026 12:58:28 GMT</pubDate>
    </item>    <item>
      <title>0.3.0</title>
      <link>https://pypi.org/project/economize/0.3.0/</link>
      <description>Composable efficiency techniques (cross-layer jump drafting, early exit, speculative decoding, ...) for Hugging Face causal LMs.</description>
<author>f.laitenberger@gmail.com</author>      <pubDate>Sun, 11 Oct 2026 09:40:12 GMT</pubDate>
    </item>  </channel>
</rss>