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    <title>PyPI recent updates for HiFT</title>
    <link>https://pypi.org/project/hift/</link>
    <description>Recent updates to the Python Package Index for HiFT</description>
    <language>en</language>    <item>
      <title>0.0.5</title>
      <link>https://pypi.org/project/hift/0.0.5/</link>
      <description>PyTorch implementation of &#39;HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy&#39;, a memory-efficient approach to adapt a large pre-trained deep learning model.</description>
<author>misonsky@163.com</author>      <pubDate>Sat, 25 May 2024 22:40:05 GMT</pubDate>
    </item>    <item>
      <title>0.0.4</title>
      <link>https://pypi.org/project/hift/0.0.4/</link>
      <description>PyTorch implementation of &#39;HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy&#39;, a memory-efficient approach to adapt a large pre-trained deep learning model.</description>
<author>misonsky@163.com</author>      <pubDate>Tue, 21 May 2024 01:02:39 GMT</pubDate>
    </item>    <item>
      <title>0.0.3</title>
      <link>https://pypi.org/project/hift/0.0.3/</link>
      <description>PyTorch implementation of &#39;HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy&#39;, a memory-efficient approach to adapt a large pre-trained deep learning model.</description>
<author>misonsky@163.com</author>      <pubDate>Wed, 15 May 2024 12:42:18 GMT</pubDate>
    </item>    <item>
      <title>0.0.2</title>
      <link>https://pypi.org/project/hift/0.0.2/</link>
      <description>PyTorch implementation of &#39;HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy&#39;, a memory-efficient approach to adapt a large pre-trained deep learning model.</description>
<author>misonsky@163.com</author>      <pubDate>Sun, 12 May 2024 21:41:03 GMT</pubDate>
    </item>    <item>
      <title>0.0.1</title>
      <link>https://pypi.org/project/hift/0.0.1/</link>
      <description>PyTorch implementation of &#39;HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy&#39;, a memory-efficient approach to adapt a large pre-trained deep learning model.</description>
<author>misonsky@163.com</author>      <pubDate>Wed, 01 May 2024 16:17:11 GMT</pubDate>
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