mirror of
https://github.com/ikawrakow/ik_llama.cpp.git
synced 2026-01-26 17:20:01 +00:00
0ceeb11721
* Merging mainline - WIP * Merging mainline - WIP AVX2 and CUDA appear to work. CUDA performance seems slightly (~1-2%) lower as it is so often the case with llama.cpp/ggml after some "improvements" have been made. * Merging mainline - fix Metal * Remove check --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
36 lines
864 B
Docker
36 lines
864 B
Docker
ARG UBUNTU_VERSION=22.04
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# This needs to generally match the container host's environment.
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ARG CUDA_VERSION=11.7.1
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# Target the CUDA build image
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ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
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# Target the CUDA runtime image
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ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
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FROM ${BASE_CUDA_DEV_CONTAINER} AS build
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# Unless otherwise specified, we make a fat build.
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ARG CUDA_DOCKER_ARCH=all
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RUN apt-get update && \
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apt-get install -y build-essential git
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WORKDIR /app
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COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV GGML_CUDA=1
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RUN make -j$(nproc) llama-cli
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FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
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RUN apt-get update && \
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apt-get install -y libgomp1
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COPY --from=build /app/llama-cli /llama-cli
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ENTRYPOINT [ "/llama-cli" ]
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