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base repository: SciSharp/LLamaSharp
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  • 3 commits
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Commits on Dec 14, 2023

  1. Using CUDA while decoupling from the CUDA Toolkit as a hard-dependency 

    Using CUDA while decoupling from the CUDA Toolkit as a hard-dependency

Possible solution for #350

Adding an alternative, fallback method of detection system-supported cuda version to make CUDA Toolkit installation optional. Technically, it uses output of the command line tool "nvidia-smi" (preinstalled with nvidia drivers), which also contains information about cuda version supported on system.

Can confirm it works only on Windows, but I suppose that similar approach can be utilized for Linux and MacOS as well. Didn't touch the code for these 2 platforms, nevertheless.

After that, cuda can be utilized simply by putting nvidia libraries from llama.cpp original repo, "bin-win-cublas-cu12.2.0-x64.zip" asset to the root folder of the built program. For example, to folder: "\LLama.Examples\bin\Debug\net8.0\".
    @Onkitova
    Onkitova committed Dec 14, 2023
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Commits on Dec 15, 2023

  1. Merge pull request #365 from Onkitova/preview 

    feat: using CUDA while decoupling from the CUDA Toolkit as a hard-dependency
    @AsakusaRinne
    AsakusaRinne authored Dec 15, 2023
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Commits on Dec 16, 2023

  1. Merge branch 'master' of github.com:SciSharp/LLamaSharp into preview

    @AsakusaRinne
    AsakusaRinne committed Dec 16, 2023
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