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gnu: llama-cpp: Use OpenBLAS.
For faster prompt processing, OpenBLAS is recommended by https://github.com/ggerganov/llama.cpp * gnu/packages/machine-learning.scm (llama-cpp)[arguments]: Add #:configure-flags. [native-inputs]: Add pkg-config. [propagated-inputs]: Add openblas. Change-Id: Iaf6f22252da13e2d6f503992878b35b0da7de0aa Signed-off-by: Christopher Baines <mail@cbaines.net>
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Christopher Baines
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@@ -541,6 +541,8 @@ Performance is achieved by using the LLVM JIT compiler.")
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(build-system cmake-build-system)
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(arguments
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(list
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#:configure-flags
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'(list "-DLLAMA_BLAS=ON" "-DLLAMA_BLAS_VENDOR=OpenBLAS")
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#:modules '((ice-9 textual-ports)
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(guix build utils)
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((guix build python-build-system) #:prefix python:)
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@@ -575,8 +577,9 @@ Performance is achieved by using the LLVM JIT compiler.")
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(lambda _
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(copy-file "bin/main" (string-append #$output "/bin/llama")))))))
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(inputs (list python))
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(native-inputs (list pkg-config))
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(propagated-inputs
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(list python-numpy python-pytorch python-sentencepiece))
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(list python-numpy python-pytorch python-sentencepiece openblas))
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(home-page "https://github.com/ggerganov/llama.cpp")
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(synopsis "Port of Facebook's LLaMA model in C/C++")
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(description "This package provides a port to Facebook's LLaMA collection
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