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<Platforms >AnyCPU;x64;Arm64</Platforms >
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<AllowUnsafeBlocks >True</AllowUnsafeBlocks >
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- <Version >0.11.2 </Version >
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+ <Version >0.12.0 </Version >
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<Authors >Rinne, Martin Evans, jlsantiago and all the other contributors in https://github.com/SciSharp/LLamaSharp/graphs/contributors.</Authors >
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<Company >SciSharp STACK</Company >
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<GeneratePackageOnBuild >true</GeneratePackageOnBuild >
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With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
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</Description >
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<PackageReleaseNotes >
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- LLamaSharp 0.11.2 fixed the performance issue of LLaVA on GPU and improved the log suppression .
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+ Updated llama.cpp version to include better support for LLama3 tokenization .
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</PackageReleaseNotes >
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<PackageLicenseExpression >MIT</PackageLicenseExpression >
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<PackageOutputPath >packages</PackageOutputPath >
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