mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-11-11 13:30:35 +00:00
parent
a95631ee97
commit
0e814dfc42
@ -27,7 +27,7 @@ COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV LLAMA_CUDA=1
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ENV GGML_CUDA=1
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# Enable cURL
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ENV LLAMA_CURL=1
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@ -36,7 +36,7 @@ COPY . .
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# Set nvcc architecture
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ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
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# Enable ROCm
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ENV LLAMA_HIPBLAS=1
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ENV GGML_HIPBLAS=1
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ENV CC=/opt/rocm/llvm/bin/clang
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ENV CXX=/opt/rocm/llvm/bin/clang++
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@ -21,7 +21,7 @@ COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV LLAMA_CUDA=1
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ENV GGML_CUDA=1
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RUN make -j$(nproc) llama-cli
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@ -2,7 +2,7 @@ ARG ONEAPI_VERSION=2024.1.1-devel-ubuntu22.04
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FROM intel/oneapi-basekit:$ONEAPI_VERSION as build
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ARG LLAMA_SYCL_F16=OFF
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ARG GGML_SYCL_F16=OFF
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RUN apt-get update && \
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apt-get install -y git
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@ -10,11 +10,11 @@ WORKDIR /app
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COPY . .
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RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
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echo "LLAMA_SYCL_F16 is set" && \
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export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
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RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
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echo "GGML_SYCL_F16 is set" && \
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export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
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fi && \
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cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
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cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
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cmake --build build --config Release --target llama-cli
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FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
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@ -36,7 +36,7 @@ COPY . .
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# Set nvcc architecture
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ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
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# Enable ROCm
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ENV LLAMA_HIPBLAS=1
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ENV GGML_HIPBLAS=1
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ENV CC=/opt/rocm/llvm/bin/clang
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ENV CXX=/opt/rocm/llvm/bin/clang++
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@ -14,7 +14,7 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key
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# Build it
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WORKDIR /app
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COPY . .
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RUN cmake -B build -DLLAMA_VULKAN=1 && \
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RUN cmake -B build -DGGML_VULKAN=1 && \
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cmake --build build --config Release --target llama-cli
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# Clean up
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@ -1,84 +0,0 @@
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# SRPM for building from source and packaging an RPM for RPM-based distros.
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# https://docs.fedoraproject.org/en-US/quick-docs/creating-rpm-packages
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# Built and maintained by John Boero - boeroboy@gmail.com
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# In honor of Seth Vidal https://www.redhat.com/it/blog/thank-you-seth-vidal
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# Notes for llama.cpp:
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# 1. Tags are currently based on hash - which will not sort asciibetically.
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# We need to declare standard versioning if people want to sort latest releases.
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# 2. Builds for CUDA/OpenCL support are separate, with different depenedencies.
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# 3. NVidia's developer repo must be enabled with nvcc, cublas, clblas, etc installed.
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# Example: https://developer.download.nvidia.com/compute/cuda/repos/fedora37/x86_64/cuda-fedora37.repo
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# 4. OpenCL/CLBLAST support simply requires the ICD loader and basic opencl libraries.
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# It is up to the user to install the correct vendor-specific support.
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Name: llama.cpp-clblast
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Version: %( date "+%%Y%%m%%d" )
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Release: 1%{?dist}
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Summary: OpenCL Inference of LLaMA model in C/C++
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License: MIT
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Source0: https://github.com/ggerganov/llama.cpp/archive/refs/heads/master.tar.gz
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BuildRequires: coreutils make gcc-c++ git mesa-libOpenCL-devel clblast-devel
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Requires: clblast
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URL: https://github.com/ggerganov/llama.cpp
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%define debug_package %{nil}
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%define source_date_epoch_from_changelog 0
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%description
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CPU inference for Meta's Lllama2 models using default options.
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%prep
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%setup -n llama.cpp-master
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%build
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make -j LLAMA_CLBLAST=1
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%install
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mkdir -p %{buildroot}%{_bindir}/
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cp -p llama-cli %{buildroot}%{_bindir}/llama-clblast-cli
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cp -p llama-server %{buildroot}%{_bindir}/llama-clblast-server
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cp -p llama-simple %{buildroot}%{_bindir}/llama-clblast-simple
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mkdir -p %{buildroot}/usr/lib/systemd/system
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%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llamaclblast.service
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[Unit]
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Description=Llama.cpp server, CPU only (no GPU support in this build).
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After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.target
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[Service]
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Type=simple
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EnvironmentFile=/etc/sysconfig/llama
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ExecStart=/usr/bin/llama-clblast-server $LLAMA_ARGS
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ExecReload=/bin/kill -s HUP $MAINPID
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Restart=never
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[Install]
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WantedBy=default.target
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EOF
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mkdir -p %{buildroot}/etc/sysconfig
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%{__cat} <<EOF > %{buildroot}/etc/sysconfig/llama
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LLAMA_ARGS="-m /opt/llama2/ggml-model-f32.bin"
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EOF
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%clean
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rm -rf %{buildroot}
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rm -rf %{_builddir}/*
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%files
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%{_bindir}/llama-clblast-cli
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%{_bindir}/llama-clblast-server
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%{_bindir}/llama-clblast-simple
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/usr/lib/systemd/system/llamaclblast.service
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%config /etc/sysconfig/llama
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%pre
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%post
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%preun
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%postun
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%changelog
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@ -32,7 +32,7 @@ CPU inference for Meta's Lllama2 models using default options.
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%setup -n llama.cpp-master
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%build
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make -j LLAMA_CUDA=1
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make -j GGML_CUDA=1
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%install
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mkdir -p %{buildroot}%{_bindir}/
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@ -21,7 +21,7 @@ COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV LLAMA_CUDA=1
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ENV GGML_CUDA=1
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# Enable cURL
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ENV LLAMA_CURL=1
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@ -2,7 +2,7 @@ ARG ONEAPI_VERSION=2024.1.1-devel-ubuntu22.04
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FROM intel/oneapi-basekit:$ONEAPI_VERSION as build
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ARG LLAMA_SYCL_F16=OFF
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ARG GGML_SYCL_F16=OFF
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RUN apt-get update && \
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apt-get install -y git libcurl4-openssl-dev
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@ -10,11 +10,11 @@ WORKDIR /app
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COPY . .
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RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
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echo "LLAMA_SYCL_F16 is set" && \
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export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
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RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
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echo "GGML_SYCL_F16 is set" && \
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export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
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fi && \
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cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
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cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
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cmake --build build --config Release --target llama-server
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FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
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@ -36,7 +36,7 @@ COPY . .
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# Set nvcc architecture
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ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
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# Enable ROCm
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ENV LLAMA_HIPBLAS=1
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ENV GGML_HIPBLAS=1
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ENV CC=/opt/rocm/llvm/bin/clang
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ENV CXX=/opt/rocm/llvm/bin/clang++
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@ -14,7 +14,7 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key
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# Build it
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WORKDIR /app
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COPY . .
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RUN cmake -B build -DLLAMA_VULKAN=1 -DLLAMA_CURL=1 && \
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RUN cmake -B build -DGGML_VULKAN=1 -DLLAMA_CURL=1 && \
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cmake --build build --config Release --target llama-server
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# Clean up
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