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  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the paddle frontend for OpenVINO.</description>
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  <description>MeCab is a high-performance morphological analysis engine for Japanese text.
It segments sentences into tokens and assigns parts of speech, readings and
other linguistic annotations. Originally developed at the University of Kyoto,
it uses conditional random fields for statistical analysis and supports custom
dictionaries.</description>
  <packager></packager>
  <url>https://github.com/taku910/mecab</url>
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  <description>MeCab is a high-performance morphological analysis engine for Japanese text.
It segments sentences into tokens and assigns parts of speech, readings and
other linguistic annotations. Originally developed at the University of Kyoto,
it uses conditional random fields for statistical analysis and supports custom
dictionaries.</description>
  <packager></packager>
  <url>https://github.com/taku910/mecab</url>
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<package type="rpm">
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  <description>IPA dictionary for the MeCab morphological analysis engine. This is the
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  <description>IPA dictionary for the MeCab morphological analysis engine. This is the
standard dictionary for Japanese text analysis.</description>
  <packager></packager>
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  <description>JUMAN dictionary for the MeCab morphological analysis engine. It provides
an alternative analysis scheme based on the JUMAN grammar and is suitable
for research and linguistic applications.</description>
  <packager></packager>
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  <description>JUMAN dictionary for the MeCab morphological analysis engine. It provides
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for research and linguistic applications.</description>
  <packager></packager>
  <url>https://github.com/taku910/mecab</url>
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It offers a command-line interface and a RESTful API.
New models can be created or existing ones modified in the
Ollama library using the Modelfile syntax.
Source model weights found on Hugging Face and similar sites
can be imported.</description>
  <packager></packager>
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It offers a command-line interface and a RESTful API.
New models can be created or existing ones modified in the
Ollama library using the Modelfile syntax.
Source model weights found on Hugging Face and similar sites
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<package type="rpm">
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  <arch>src</arch>
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It offers a command-line interface and a RESTful API.
New models can be created or existing ones modified in the
Ollama library using the Modelfile syntax.
Source model weights found on Hugging Face and similar sites
can be imported.</description>
  <packager></packager>
  <url>https://ollama.com</url>
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<package type="rpm">
  <name>ollama-vulkan</name>
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  <description>Ollama plugin module using Vulkan.</description>
  <packager></packager>
  <url>https://ollama.com</url>
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accelerator. It is compatible with many popular ML/DNN frameworks,
including PyTorch, TensorFlow/Keras, scikit-learn, and more.</description>
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for developing applications against ONNX Runtime.</description>
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<package type="rpm">
  <name>openvino</name>
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  <summary>A toolkit for optimizing and deploying AI inference</summary>
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  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
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</package>
<package type="rpm">
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  <summary>Automatic batch software plugin for OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the automatic batch software plugin for OpenVINO.</description>
  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
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<package type="rpm">
  <name>openvino-auto-plugin</name>
  <arch>x86_64</arch>
  <version epoch="0" ver="2026.2.0" rel="62.4"/>
  <checksum type="sha512" pkgid="YES">6e8535ef6f05b1d7121680c3492c06e343e53c6a90d17022bb08f0c907b2293d13a7e466727922a862bbd2a52a47bffd7d8a5eaeae2a6ee928ba758f665742f2</checksum>
  <summary>Auto / Multi software plugin for OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the Auto / Multi software plugin for OpenVINO.</description>
  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
  <time file="1782360087" build="1780480904"/>
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    <rpm:vendor>obs://build.opensuse.org/home:jloehel</rpm:vendor>
    <rpm:group>Unspecified</rpm:group>
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      <rpm:entry name="libopenvino_auto_plugin.so()(64bit)"/>
      <rpm:entry name="openvino-auto-plugin" flags="EQ" epoch="0" ver="2026.2.0" rel="62.4"/>
      <rpm:entry name="openvino-auto-plugin(x86-64)" flags="EQ" epoch="0" ver="2026.2.0" rel="62.4"/>
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      <rpm:entry name="libgcc_s.so.1()(64bit)"/>
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      <rpm:entry name="libgcc_s.so.1(GCC_3.3.1)(64bit)"/>
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      <rpm:entry name="libc.so.6(GLIBC_2.38)(64bit)"/>
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</package>
<package type="rpm">
  <name>openvino-devel</name>
  <arch>x86_64</arch>
  <version epoch="0" ver="2026.2.0" rel="62.4"/>
  <checksum type="sha512" pkgid="YES">a83119133416b641f90fa160a7985bfe865fd0bfcca702402746a6e8c639addce53899fb5606c9e8a015629e646023695f69306c6a62945589ccdc4b513566cf</checksum>
  <summary>Headers and sources for OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the headers and sources for developing applications with
OpenVINO.</description>
  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
  <time file="1782360087" build="1780480904"/>
  <size package="353149" installed="1865964" archive="1952200"/>
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    <rpm:vendor>obs://build.opensuse.org/home:jloehel</rpm:vendor>
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      <rpm:entry name="libopenvino_c2620" flags="EQ" epoch="0" ver="2026.2.0"/>
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      <rpm:entry name="pkgconfig(OpenCL-Headers)"/>
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      <rpm:entry name="pkgconfig(ocl-icd)"/>
      <rpm:entry name="pkgconfig(protobuf)"/>
      <rpm:entry name="pkgconfig(pugixml)"/>
      <rpm:entry name="pkgconfig(snappy)"/>
      <rpm:entry name="pkgconfig(tbb)"/>
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    <rpm:recommends>
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      <rpm:entry name="openvino-auto-plugin" flags="EQ" epoch="0" ver="2026.2.0"/>
      <rpm:entry name="openvino-hetero-plugin" flags="EQ" epoch="0" ver="2026.2.0"/>
      <rpm:entry name="openvino-intel-cpu-plugin" flags="EQ" epoch="0" ver="2026.2.0"/>
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</package>
<package type="rpm">
  <name>openvino-hetero-plugin</name>
  <arch>x86_64</arch>
  <version epoch="0" ver="2026.2.0" rel="62.4"/>
  <checksum type="sha512" pkgid="YES">4586205d2293127deb20a7320f893ecc119cdbc2a3de35ae09c3f759d2d284e2f780de59db4fbfceecb5b84c4af7e40026d300e163c30ac002e2fa977c005952</checksum>
  <summary>Hetero frontend for Intel OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the hetero frontend for OpenVINO.</description>
  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
  <time file="1782360087" build="1780480904"/>
  <size package="230159" installed="589496" archive="589912"/>
  <location href="x86_64/openvino-hetero-plugin-2026.2.0-62.4.x86_64.rpm"/>
  <format>
    <rpm:license>Apache-2.0 AND BSD-2-Clause AND BSD-3-Clause AND HPND AND JSON AND MIT AND OFL-1.1 AND Zlib</rpm:license>
    <rpm:vendor>obs://build.opensuse.org/home:jloehel</rpm:vendor>
    <rpm:group>Unspecified</rpm:group>
    <rpm:buildhost>reproducible</rpm:buildhost>
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      <rpm:entry name="libopenvino.so.2620()(64bit)"/>
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</package>
<package type="rpm">
  <name>openvino-intel-cpu-plugin</name>
  <arch>x86_64</arch>
  <version epoch="0" ver="2026.2.0" rel="62.4"/>
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  <summary>Intel CPU plugin for OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the intel CPU plugin for OpenVINO for x86_64 x86_64_v2 x86_64_v3 x86_64_v4 amd64 em64t archs.</description>
  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
  <time file="1782360087" build="1780480904"/>
  <size package="12965288" installed="81119008" archive="81119428"/>
  <location href="x86_64/openvino-intel-cpu-plugin-2026.2.0-62.4.x86_64.rpm"/>
  <format>
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</package>
<package type="rpm">
  <name>openvino-intel-gpu-plugin</name>
  <arch>x86_64</arch>
  <version epoch="0" ver="2026.2.0" rel="62.4"/>
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  <summary>Intel GPU plugin for OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the intel GPU plugin for OpenVINO for x86_64 x86_64_v2 x86_64_v3 x86_64_v4 amd64 em64t archs.</description>
  <packager></packager>
  <url>https://github.com/openvinotoolkit/openvino</url>
  <time file="1782360087" build="1780480904"/>
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<package type="rpm">
  <name>openvino-intel-npu-plugin</name>
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  <summary>Intel NPU plugin for OpenVINO toolkit</summary>
  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides the intel NPU plugin for OpenVINO for x86_64 x86_64_v2 x86_64_v3 x86_64_v4 amd64 em64t archs.</description>
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  <url>https://github.com/openvinotoolkit/openvino</url>
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  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides some samples for use with openVINO.</description>
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  <url>https://github.com/openvinotoolkit/openvino</url>
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<package type="rpm">
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  <description>OpenVINO is an open-source toolkit for optimizing and deploying AI inference.

This package provides a Python module for interfacing with openVINO toolkit.</description>
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  <url>https://github.com/openvinotoolkit/openvino</url>
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      <rpm:entry name="libstdc++.so.6(GLIBCXX_3.4.9)(64bit)"/>
      <rpm:entry name="libtvm_ffi.so()(64bit)"/>
      <rpm:entry name="python(abi)" flags="EQ" epoch="0" ver="3.14"/>
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      <rpm:entry name="libc.so.6(GLIBC_2.38)(64bit)"/>
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  <name>tvm</name>
  <arch>src</arch>
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  <description>TVM is a deep learning compiler stack for CPUs, GPUs, and specialized accelerators.</description>
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  <url>https://tvm.apache.org/</url>
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      <rpm:entry name="pkgconfig(glfw3)"/>
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      <rpm:entry name="rang-devel"/>
      <rpm:entry name="spirv-headers"/>
      <rpm:entry name="spirv-tools"/>
      <rpm:entry name="spirv-tools-devel"/>
      <rpm:entry name="vulkan-devel"/>
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</package>
<package type="rpm">
  <name>tvm-devel</name>
  <arch>x86_64</arch>
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  <summary>Headers for the TVM Deep Learning Compiler Stack</summary>
  <description>TVM is a deep learning compiler stack for CPUs, GPUs, and specialized accelerators.

This package contains the headers.</description>
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  <url>https://tvm.apache.org/</url>
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  <size package="306820" installed="1823837" archive="1858152"/>
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    <rpm:group>Unspecified</rpm:group>
    <rpm:buildhost>reproducible</rpm:buildhost>
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<package type="rpm">
  <name>tvmc</name>
  <arch>x86_64</arch>
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  <summary>TVM command line driver</summary>
  <description>TVMC is a tool that exposes TVM features such as auto-tuning, compiling,
profiling and execution of models, via a command line interface.</description>
  <packager></packager>
  <url>https://tvm.apache.org/</url>
  <time file="1781827085" build="1781608949"/>
  <size package="10684" installed="42" archive="296"/>
  <location href="x86_64/tvmc-0.24.0-98.1.x86_64.rpm"/>
  <format>
    <rpm:license>Apache-2.0</rpm:license>
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    <rpm:requires>
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      <rpm:entry name="python3-tvm" flags="EQ" epoch="0" ver="0.24.0"/>
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    <rpm:recommends>
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      <rpm:entry name="python3-onnx"/>
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    <file>/usr/bin/tvmc</file>
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</package>
</metadata>