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34 changed files with 766 additions and 25323 deletions
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@ -18,7 +18,7 @@ See the [development documentation](./docs/development.md) for instructions on h
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* New features: new features (e.g. API fields, environment variables) add surface area to Ollama and make it harder to maintain in the long run as they cannot be removed without potentially breaking users in the future.
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* Refactoring: large code improvements are important, but can be harder or take longer to review and merge.
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* Documentation: small updates to fill in or dorrect missing documentation is helpful, however large documentation additions can be hard to maintain over time.
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* Documentation: small updates to fill in or correct missing documentation is helpful, however large documentation additions can be hard to maintain over time.
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### Issues that may not be accepted
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252
Dockerfile
252
Dockerfile
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@ -1,217 +1,61 @@
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ARG GOLANG_VERSION=1.22.5
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ARG CMAKE_VERSION=3.22.1
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ARG CUDA_VERSION_11=11.3.1
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ARG CUDA_V11_ARCHITECTURES="50;52;53;60;61;62;70;72;75;80;86"
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ARG CUDA_VERSION_12=12.4.0
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ARG CUDA_V12_ARCHITECTURES="60;61;62;70;72;75;80;86;87;89;90;90a"
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ARG ROCM_VERSION=6.1.2
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# Build stage
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FROM golang:1.22-bookworm as build
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# Copy the minimal context we need to run the generate scripts
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FROM scratch AS llm-code
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COPY .git .git
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COPY .gitmodules .gitmodules
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COPY llm llm
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# Install necessary dependencies
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RUN apt update && apt install -y \
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wget \
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gnupg \
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software-properties-common \
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git \
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apt-utils
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FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION_11-devel-centos7 AS cuda-11-build-amd64
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ARG CMAKE_VERSION
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COPY ./scripts/rh_linux_deps.sh /
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RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
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ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
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COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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ARG CGO_CFLAGS
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ARG CUDA_V11_ARCHITECTURES
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ENV GOARCH amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 \
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OLLAMA_SKIP_CPU_GENERATE=1 \
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CMAKE_CUDA_ARCHITECTURES="${CUDA_V11_ARCHITECTURES}" \
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CUDA_VARIANT="_v11" \
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bash gen_linux.sh
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# Install Intel oneAPI
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RUN wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null && \
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echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | tee /etc/apt/sources.list.d/oneAPI.list && \
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apt update && \
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apt install -y --no-install-recommends \
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intel-oneapi-mkl \
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intel-oneapi-compiler-dpcpp-cpp \
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intel-oneapi-mkl-devel \
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gcc \
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g++ \
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pkg-config \
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cmake
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FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION_12-devel-centos7 AS cuda-12-build-amd64
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ARG CMAKE_VERSION
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COPY ./scripts/rh_linux_deps.sh /
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RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
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ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
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COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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ARG CGO_CFLAGS
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ARG CUDA_V12_ARCHITECTURES
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ENV GOARCH amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 \
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OLLAMA_SKIP_CPU_GENERATE=1 \
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CMAKE_CUDA_ARCHITECTURES="${CUDA_V12_ARCHITECTURES}" \
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CUDA_VARIANT="_v12" \
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OLLAMA_CUSTOM_CUDA_DEFS="-DGGML_CUDA_USE_GRAPHS=on" \
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bash gen_linux.sh
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WORKDIR /app
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FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION_11-devel-rockylinux8 AS cuda-11-build-server-arm64
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ARG CMAKE_VERSION
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COPY ./scripts/rh_linux_deps.sh /
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RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
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ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
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COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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ARG CGO_CFLAGS
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ARG CUDA_V11_ARCHITECTURES
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ENV GOARCH arm64
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RUN OLLAMA_SKIP_STATIC_GENERATE=1 \
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OLLAMA_SKIP_CPU_GENERATE=1 \
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CMAKE_CUDA_ARCHITECTURES="${CUDA_V11_ARCHITECTURES}" \
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CUDA_VARIANT="_v11" \
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bash gen_linux.sh
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ARG GIN_MODE=release
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FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION_12-devel-rockylinux8 AS cuda-12-build-server-arm64
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ARG CMAKE_VERSION
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COPY ./scripts/rh_linux_deps.sh /
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RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
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ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
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COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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ARG CGO_CFLAGS
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ARG CUDA_V12_ARCHITECTURES
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ENV GOARCH arm64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 \
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OLLAMA_SKIP_CPU_GENERATE=1 \
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CMAKE_CUDA_ARCHITECTURES="${CUDA_V12_ARCHITECTURES}" \
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CUDA_VARIANT="_v12" \
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OLLAMA_CUSTOM_CUDA_DEFS="-DGGML_CUDA_USE_GRAPHS=on" \
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bash gen_linux.sh
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ADD . .
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RUN . /opt/intel/oneapi/setvars.sh && \
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OLLAMA_CUSTOM_CPU_DEFS="-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_NATIVE=ON" go generate ./... && \
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go build -ldflags="-s -w"
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FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS rocm-build-amd64
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ARG CMAKE_VERSION
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COPY ./scripts/rh_linux_deps.sh /
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RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
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ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
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ENV LIBRARY_PATH /opt/amdgpu/lib64
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COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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ARG CGO_CFLAGS
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ARG AMDGPU_TARGETS
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ENV GOARCH amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 bash gen_linux.sh
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RUN mkdir -p ../../dist/linux-amd64-rocm/lib/ollama && \
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(cd /opt/rocm/lib && tar cf - rocblas/library) | (cd ../../dist/linux-amd64-rocm/lib/ollama && tar xf - )
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FROM debian:bookworm-slim
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FROM --platform=linux/amd64 centos:7 AS cpu-builder-amd64
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ARG CMAKE_VERSION
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ARG GOLANG_VERSION
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COPY ./scripts/rh_linux_deps.sh /
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RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
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ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
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COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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ARG OLLAMA_CUSTOM_CPU_DEFS
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ARG CGO_CFLAGS
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ENV GOARCH amd64
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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RUN apt update && apt install -y --no-install-recommends \
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wget \
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gnupg \
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software-properties-common \
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supervisor && \
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wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null && \
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echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | tee /etc/apt/sources.list.d/oneAPI.list && \
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apt update && \
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apt install -y --no-install-recommends intel-oneapi-runtime-libs && \
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apt clean && \
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rm -rf /var/lib/apt/lists/*
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FROM --platform=linux/amd64 cpu-builder-amd64 AS static-build-amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_CPU_TARGET="static" bash gen_linux.sh
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FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" bash gen_linux.sh
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FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" bash gen_linux.sh
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FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" bash gen_linux.sh
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WORKDIR /app
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FROM --platform=linux/arm64 rockylinux:8 AS cpu-builder-arm64
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ARG CMAKE_VERSION
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||||
ARG GOLANG_VERSION
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||||
COPY ./scripts/rh_linux_deps.sh /
|
||||
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
|
||||
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
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||||
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
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ARG OLLAMA_CUSTOM_CPU_DEFS
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ARG CGO_CFLAGS
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ENV GOARCH arm64
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WORKDIR /go/src/github.com/ollama/ollama/llm/generate
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COPY --from=build /app/supervisord.conf /app/supervisord.conf
|
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COPY --from=build /app/ollama /app/ollama
|
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COPY --from=build /app/run_model.sh /app/run_model.sh
|
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COPY --from=build /app/serve.sh /app/serve.sh
|
||||
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||||
FROM --platform=linux/arm64 cpu-builder-arm64 AS static-build-arm64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_CPU_TARGET="static" bash gen_linux.sh
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FROM --platform=linux/arm64 cpu-builder-arm64 AS cpu-build-arm64
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RUN --mount=type=cache,target=/root/.ccache \
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OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" bash gen_linux.sh
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ENV MODEL_NAME="llama"
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ENV OLLAMA_HOST="0.0.0.0:8080"
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EXPOSE 8080
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# Intermediate stage used for ./scripts/build_linux.sh
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FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
|
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ENV CGO_ENABLED 1
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WORKDIR /go/src/github.com/ollama/ollama
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COPY . .
|
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COPY --from=static-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=cpu_avx-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=cpu_avx2-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=cuda-11-build-amd64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=cuda-11-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=cuda-12-build-amd64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=cuda-12-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/dist/ dist/
|
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COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
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ARG GOFLAGS
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ARG CGO_CFLAGS
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RUN --mount=type=cache,target=/root/.ccache \
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go build -trimpath -o dist/linux-amd64/bin/ollama .
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# Intermediate stage used for ./scripts/build_linux.sh
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FROM --platform=linux/arm64 cpu-build-arm64 AS build-arm64
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ENV CGO_ENABLED 1
|
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ARG GOLANG_VERSION
|
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WORKDIR /go/src/github.com/ollama/ollama
|
||||
COPY . .
|
||||
COPY --from=static-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=cuda-11-build-server-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=cuda-11-build-server-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
COPY --from=cuda-12-build-server-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
|
||||
COPY --from=cuda-12-build-server-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
|
||||
ARG GOFLAGS
|
||||
ARG CGO_CFLAGS
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||||
RUN --mount=type=cache,target=/root/.ccache \
|
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go build -trimpath -o dist/linux-arm64/bin/ollama .
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||||
# Strip out ROCm dependencies to keep the primary image lean
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||||
FROM --platform=linux/amd64 ubuntu:22.04 as amd64-libs-without-rocm
|
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COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /scratch/
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||||
RUN cd /scratch/ollama/ && rm -rf rocblas libamd* libdrm* libroc* libhip* libhsa*
|
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||||
# Runtime stages
|
||||
FROM --platform=linux/amd64 ubuntu:22.04 as runtime-amd64
|
||||
COPY --from=amd64-libs-without-rocm /scratch/ /lib/
|
||||
RUN apt-get update && apt-get install -y ca-certificates
|
||||
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
|
||||
|
||||
FROM --platform=linux/arm64 ubuntu:22.04 as runtime-arm64
|
||||
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
|
||||
RUN apt-get update && apt-get install -y ca-certificates
|
||||
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/bin/ /bin/
|
||||
|
||||
# Radeon images are much larger so we keep it distinct from the CPU/CUDA image
|
||||
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete as runtime-rocm
|
||||
RUN update-pciids
|
||||
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
|
||||
RUN ln -s /opt/rocm/lib /lib/ollama
|
||||
EXPOSE 11434
|
||||
ENV OLLAMA_HOST 0.0.0.0
|
||||
|
||||
ENTRYPOINT ["/bin/ollama"]
|
||||
CMD ["serve"]
|
||||
|
||||
FROM runtime-$TARGETARCH
|
||||
EXPOSE 11434
|
||||
ENV OLLAMA_HOST 0.0.0.0
|
||||
ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
|
||||
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
|
||||
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
||||
ENV NVIDIA_VISIBLE_DEVICES=all
|
||||
|
||||
ENTRYPOINT ["/bin/ollama"]
|
||||
CMD ["serve"]
|
||||
CMD ["supervisord", "-c", "/app/supervisord.conf"]
|
||||
|
|
25
README.md
25
README.md
|
@ -295,13 +295,23 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
|||
- [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
|
||||
- [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
|
||||
- [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
|
||||
- [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in discord )
|
||||
- [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
|
||||
- [Painting Droid](https://github.com/mateuszmigas/painting-droid) (Painting app with AI integrations)
|
||||
- [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
|
||||
- [AI Studio](https://github.com/MindWorkAI/AI-Studio)
|
||||
- [Sidellama](https://github.com/gyopak/sidellama) (browser-based LLM client)
|
||||
- [LLMStack](https://github.com/trypromptly/LLMStack) (No-code multi-agent framework to build LLM agents and workflows)
|
||||
- [BoltAI for Mac](https://boltai.com) (AI Chat Client for Mac)
|
||||
- [Harbor](https://github.com/av/harbor) (Containerized LLM Toolkit with Ollama as default backend)
|
||||
- [Go-CREW](https://www.jonathanhecl.com/go-crew/) (Powerful Offline RAG in Golang)
|
||||
- [PartCAD](https://github.com/openvmp/partcad/) (CAD model generation with OpenSCAD and CadQuery)
|
||||
- [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot and Ollama4j
|
||||
- [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models.
|
||||
- [Claude Dev](https://github.com/saoudrizwan/claude-dev) - VSCode extension for multi-file/whole-repo coding
|
||||
- [Cherry Studio](https://github.com/kangfenmao/cherry-studio) (Desktop client with Ollama support)
|
||||
- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy focused LLM chat interface with optional encryption)
|
||||
- [Archyve](https://github.com/nickthecook/archyve) (RAG-enabling document library)
|
||||
|
||||
### Terminal
|
||||
|
||||
|
@ -327,6 +337,9 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
|||
- [gollama](https://github.com/sammcj/gollama)
|
||||
- [Ollama eBook Summary](https://github.com/cognitivetech/ollama-ebook-summary/)
|
||||
|
||||
### Apple Vision Pro
|
||||
- [Enchanted](https://github.com/AugustDev/enchanted)
|
||||
|
||||
### Database
|
||||
|
||||
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps)
|
||||
|
@ -335,6 +348,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
|||
### Package managers
|
||||
|
||||
- [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
|
||||
- [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/ollama)
|
||||
- [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
|
||||
- [Guix channel](https://codeberg.org/tusharhero/ollama-guix)
|
||||
- [Nix package](https://search.nixos.org/packages?channel=24.05&show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama)
|
||||
|
@ -349,11 +363,12 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
|||
- [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs)
|
||||
- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
|
||||
- [LiteLLM](https://github.com/BerriAI/litellm)
|
||||
- [OllamaFarm for Go](https://github.com/presbrey/ollamafarm)
|
||||
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
|
||||
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
|
||||
- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
|
||||
- [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp)
|
||||
- [Ollama4j for Java](https://github.com/amithkoujalgi/ollama4j)
|
||||
- [Ollama4j for Java](https://github.com/ollama4j/ollama4j)
|
||||
- [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama)
|
||||
- [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit)
|
||||
- [Ollama for Dart](https://github.com/breitburg/dart-ollama)
|
||||
|
@ -370,11 +385,16 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
|||
- [Portkey](https://portkey.ai/docs/welcome/integration-guides/ollama)
|
||||
- [PromptingTools.jl](https://github.com/svilupp/PromptingTools.jl) with an [example](https://svilupp.github.io/PromptingTools.jl/dev/examples/working_with_ollama)
|
||||
- [LlamaScript](https://github.com/Project-Llama/llamascript)
|
||||
- [Gollm](https://docs.gollm.co/examples/ollama-example)
|
||||
- [Ollamaclient for Golang](https://github.com/xyproto/ollamaclient)
|
||||
- [High-level function abstraction in Go](https://gitlab.com/tozd/go/fun)
|
||||
- [Ollama PHP](https://github.com/ArdaGnsrn/ollama-php)
|
||||
|
||||
### Mobile
|
||||
|
||||
- [Enchanted](https://github.com/AugustDev/enchanted)
|
||||
- [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
|
||||
- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy focused LLM chat interface with optional encryption)
|
||||
|
||||
### Extensions & Plugins
|
||||
|
||||
|
@ -399,11 +419,14 @@ See the [API documentation](./docs/api.md) for all endpoints.
|
|||
- [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
|
||||
- [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and Hugging Face)
|
||||
- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
|
||||
- [Plasmoid Ollama Control](https://github.com/imoize/plasmoid-ollamacontrol) (KDE Plasma extension that allows you to quickly manage/control Ollama model)
|
||||
- [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend)
|
||||
- [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)
|
||||
- [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation)
|
||||
- [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities.
|
||||
- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)
|
||||
- [vnc-lm](https://github.com/jk011ru/vnc-lm) (A containerized Discord bot with support for attachments and web links)
|
||||
- [LSP-AI](https://github.com/SilasMarvin/lsp-ai) (Open-source language server for AI-powered functionality)
|
||||
|
||||
### Supported backends
|
||||
|
||||
|
|
|
@ -1421,6 +1421,8 @@ func NewCLI() *cobra.Command {
|
|||
envVars["OLLAMA_TMPDIR"],
|
||||
envVars["OLLAMA_FLASH_ATTENTION"],
|
||||
envVars["OLLAMA_LLM_LIBRARY"],
|
||||
envVars["OLLAMA_GPU_OVERHEAD"],
|
||||
envVars["OLLAMA_LOAD_TIMEOUT"],
|
||||
})
|
||||
default:
|
||||
appendEnvDocs(cmd, envs)
|
||||
|
|
|
@ -34,10 +34,20 @@ func (p *gemma2Model) KV(t *Tokenizer) llm.KV {
|
|||
}
|
||||
|
||||
func (p *gemma2Model) Replacements() []string {
|
||||
return append(
|
||||
p.gemmaModel.Replacements(),
|
||||
return []string{
|
||||
"model.embed_tokens", "token_embd",
|
||||
"model.norm", "output_norm",
|
||||
"model.layers", "blk",
|
||||
"input_layernorm", "attn_norm",
|
||||
"self_attn.q_proj", "attn_q",
|
||||
"self_attn.k_proj", "attn_k",
|
||||
"self_attn.v_proj", "attn_v",
|
||||
"self_attn.o_proj", "attn_output",
|
||||
"mlp.gate_proj", "ffn_gate",
|
||||
"mlp.down_proj", "ffn_down",
|
||||
"mlp.up_proj", "ffn_up",
|
||||
"post_attention_layernorm", "post_attention_norm",
|
||||
"pre_feedforward_layernorm", "ffn_norm",
|
||||
"post_feedforward_layernorm", "post_ffw_norm",
|
||||
)
|
||||
}
|
||||
}
|
||||
|
|
|
@ -15,6 +15,7 @@ import (
|
|||
"os"
|
||||
"path/filepath"
|
||||
"slices"
|
||||
"strings"
|
||||
"testing"
|
||||
|
||||
"golang.org/x/exp/maps"
|
||||
|
@ -22,6 +23,12 @@ import (
|
|||
"github.com/ollama/ollama/llm"
|
||||
)
|
||||
|
||||
type tensorData struct {
|
||||
Offsets []int `json:"data_offsets"`
|
||||
Type string `json:"dtype"`
|
||||
Shape []int `json:"shape"`
|
||||
}
|
||||
|
||||
func convertFull(t *testing.T, fsys fs.FS) (*os.File, llm.KV, llm.Tensors) {
|
||||
t.Helper()
|
||||
|
||||
|
@ -96,6 +103,7 @@ func TestConvertModel(t *testing.T) {
|
|||
"Mistral-7B-Instruct-v0.2",
|
||||
"Mixtral-8x7B-Instruct-v0.1",
|
||||
"gemma-2b-it",
|
||||
"gemma-2-2b-it",
|
||||
// microsoft/Phi-3-mini-128-instruct@d548c233192db00165d842bf8edff054bb3212f8
|
||||
"Phi-3-mini-128k-instruct",
|
||||
"all-MiniLM-L6-v2",
|
||||
|
@ -140,6 +148,36 @@ func TestConvertModel(t *testing.T) {
|
|||
}
|
||||
}
|
||||
|
||||
func TestConvertInvalidTensorNames(t *testing.T) {
|
||||
f, err := os.CreateTemp(t.TempDir(), "testmodel")
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
defer f.Close()
|
||||
|
||||
tempDir := t.TempDir()
|
||||
|
||||
td := map[string]*tensorData{}
|
||||
offset := 4096
|
||||
|
||||
td["model.layers.0.self_attn.q_proj.weight"] = &tensorData{
|
||||
Offsets: []int{0, offset},
|
||||
Type: "F32",
|
||||
Shape: []int{4096, 4096},
|
||||
}
|
||||
td["blk.0.attn_q.weight"] = &tensorData{
|
||||
Offsets: []int{offset, offset * 2},
|
||||
Type: "F32",
|
||||
Shape: []int{4096, 4096},
|
||||
}
|
||||
generateSafetensorTestData(t, tempDir, td)
|
||||
|
||||
err = ConvertModel(os.DirFS(tempDir), f)
|
||||
if err == nil || !strings.HasPrefix(err.Error(), "duplicate tensor name") {
|
||||
t.Errorf("expected error but didn't get one")
|
||||
}
|
||||
}
|
||||
|
||||
func TestConvertInvalidDatatype(t *testing.T) {
|
||||
f, err := os.CreateTemp(t.TempDir(), "testmodel")
|
||||
if err != nil {
|
||||
|
@ -148,23 +186,10 @@ func TestConvertInvalidDatatype(t *testing.T) {
|
|||
defer f.Close()
|
||||
|
||||
tempDir := t.TempDir()
|
||||
generateSafetensorTestData(t, tempDir)
|
||||
|
||||
err = ConvertModel(os.DirFS(tempDir), f)
|
||||
if err == nil || err.Error() != "unsupported safetensors model" {
|
||||
t.Errorf("expected error but didn't get one")
|
||||
}
|
||||
}
|
||||
|
||||
func generateSafetensorTestData(t *testing.T, tempDir string) {
|
||||
type tensorData struct {
|
||||
Offsets []int `json:"data_offsets"`
|
||||
Type string `json:"dtype"`
|
||||
Shape []int `json:"shape"`
|
||||
}
|
||||
offset := 4096 * 14336
|
||||
|
||||
td := map[string]*tensorData{}
|
||||
offset := 4096 * 14336
|
||||
|
||||
td["model.layers.0.mlp.down_proj.weight"] = &tensorData{
|
||||
Offsets: []int{0, offset},
|
||||
Type: "I8",
|
||||
|
@ -175,8 +200,16 @@ func generateSafetensorTestData(t *testing.T, tempDir string) {
|
|||
Type: "U8",
|
||||
Shape: []int{},
|
||||
}
|
||||
generateSafetensorTestData(t, tempDir, td)
|
||||
|
||||
data, err := json.Marshal(td)
|
||||
err = ConvertModel(os.DirFS(tempDir), f)
|
||||
if err == nil || err.Error() != "unsupported safetensors model" {
|
||||
t.Errorf("expected error but didn't get one")
|
||||
}
|
||||
}
|
||||
|
||||
func generateSafetensorTestData(t *testing.T, tempDir string, tensorData map[string]*tensorData) {
|
||||
data, err := json.Marshal(tensorData)
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
|
@ -322,11 +355,6 @@ func TestConvertAdapter(t *testing.T) {
|
|||
}
|
||||
|
||||
func generateLoraTestData(t *testing.T, tempDir string) {
|
||||
type tensorData struct {
|
||||
Offsets []int `json:"data_offsets"`
|
||||
Type string `json:"dtype"`
|
||||
Shape []int `json:"shape"`
|
||||
}
|
||||
offset := 4096 * 8 * 4
|
||||
|
||||
td := map[string]*tensorData{"__metadata__": nil}
|
||||
|
|
|
@ -49,12 +49,19 @@ func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]T
|
|||
keys := maps.Keys(headers)
|
||||
slices.Sort(keys)
|
||||
|
||||
names := make(map[string]struct{}, len(keys))
|
||||
|
||||
for _, key := range keys {
|
||||
if value := headers[key]; value.Type != "" {
|
||||
// bitsandbytes quantized models are unsupported
|
||||
if len(value.Shape) == 0 {
|
||||
return nil, errors.New("unsupported safetensors model")
|
||||
}
|
||||
ggufName := replacer.Replace(key)
|
||||
if _, ok := names[ggufName]; ok {
|
||||
return nil, fmt.Errorf("duplicate tensor name '%s' was found for this model", ggufName)
|
||||
}
|
||||
names[ggufName] = struct{}{}
|
||||
ts = append(ts, safetensor{
|
||||
fs: fsys,
|
||||
path: p,
|
||||
|
@ -62,7 +69,7 @@ func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]T
|
|||
offset: safetensorsPad(n, value.Offsets[0]),
|
||||
size: safetensorsPad(n, value.Offsets[1]) - safetensorsPad(n, value.Offsets[0]),
|
||||
tensorBase: &tensorBase{
|
||||
name: replacer.Replace(key),
|
||||
name: ggufName,
|
||||
shape: value.Shape,
|
||||
},
|
||||
})
|
||||
|
|
312
convert/testdata/gemma-2-2b-it.json
vendored
Normal file
312
convert/testdata/gemma-2-2b-it.json
vendored
Normal file
|
@ -0,0 +1,312 @@
|
|||
{
|
||||
"general.architecture": "gemma2",
|
||||
"general.file_type": "1",
|
||||
"general.quantization_version": "2",
|
||||
"gemma2.block_count": "26",
|
||||
"gemma2.context_length": "8192",
|
||||
"gemma2.embedding_length": "2304",
|
||||
"gemma2.feed_forward_length": "9216",
|
||||
"gemma2.attention.head_count": "8",
|
||||
"gemma2.attention.head_count_kv": "4",
|
||||
"gemma2.attention.key_length": "256",
|
||||
"gemma2.attention.value_length": "256",
|
||||
"gemma2.attention.layer_norm_rms_epsilon": "1e-06",
|
||||
"tokenizer.ggml.model": "llama",
|
||||
"tokenizer.ggml.add_bos_token": "true",
|
||||
"tokenizer.ggml.add_eos_token": "false",
|
||||
"tokenizer.ggml.bos_token_id": "2",
|
||||
"tokenizer.ggml.eos_token_id": "1",
|
||||
"tokenizer.ggml.padding_token_id": "0",
|
||||
"tokenizer.ggml.unknown_token_id": "3",
|
||||
"tokenizer.ggml.scores": "0872465d173867d755d3ee728f882b9dc2057a0bfd596fe1e3d131522f1250d8",
|
||||
"tokenizer.ggml.token_type": "8d40143b3477df77beea4139420335ede458bf5e14102f01b0170197b55da8d8",
|
||||
"tokenizer.ggml.tokens": "c6e66de1841f04de8b8d236d461ab720a4c9b9b5414dc293a09c6e10eab45fda",
|
||||
"token_embd.weight": "64a9d30707e659e2e673656d71f5aef7a9fb9fd83bb9a77558dfc5abbe218a05",
|
||||
"blk.0.attn_k.weight": "d8b4437c5edb3cddf6af9987038e1bb2b191c4f0fce0e160d2abace717f5d5d7",
|
||||
"blk.0.attn_norm.weight": "1eb73e3f7aa8e502f6ca31cd19efbb8e4fd9a89692e13e48ac8205545a7fa7e8",
|
||||
"blk.0.attn_output.weight": "39e7b78e57d356a22dd89ce1c4d7163b970712ba756545e1703f97866cd2192e",
|
||||
"blk.0.attn_q.weight": "795058e23b6109febd9d55c89e1eebe6af0714ec8c56fd86a160876a6135ffe8",
|
||||
"blk.0.attn_v.weight": "0cd6e583d1887c020472e961bbb113fe5a0d23ae2f1c2c876fc366cdb7692b52",
|
||||
"blk.0.ffn_down.weight": "51eb4d962189e945a84e94e0dc1aad3f8f90cc1a11e18029670afcd0ea0acb1b",
|
||||
"blk.0.ffn_gate.weight": "9811a29b8ad48432925897ab21dfcb13c5cbd372aeccbbefca9b7866883b4ce3",
|
||||
"blk.0.ffn_norm.weight": "92cbf4652ef503c1de5b10f2be00b3fcf00100980cb3baa8f3013a8d8bf3d851",
|
||||
"blk.0.ffn_up.weight": "af87de21746879483ed1b374cdd76b19ba11ca2b6dbb1beba98efdf3be3e8077",
|
||||
"blk.0.post_attention_norm.weight": "32e135f1f258ffe407018899e39af1725d59d66d60022b9a21575ba160e0357a",
|
||||
"blk.0.post_ffw_norm.weight": "ba286f5ac11b07fbc986173708c66f1920427be5a6d108af38fa0a837c1c8eb6",
|
||||
"blk.1.attn_k.weight": "51584435552051f7fade76beca582b3f7190cf7fc07adcf527c2774d4b1c3901",
|
||||
"blk.1.attn_norm.weight": "6833104c7fbf35a7e799ae56c262b97fffa14789642aee14381b25acd21ed80a",
|
||||
"blk.1.attn_output.weight": "14c39481369087bf292ac9a3ab2ef166f9fe376a9f90c246653213ef264febdc",
|
||||
"blk.1.attn_q.weight": "443f64ae2229f857c69d6bebb7800b685786cb77884c3ae19d4286aeed081325",
|
||||
"blk.1.attn_v.weight": "0df482de2038f1e4c8a7733ac0ddb69ad90759dab5968b942af0155588de4c4a",
|
||||
"blk.1.ffn_down.weight": "66f30763a8bbbcaea609a0087ed75fadb5e771c06378dd2cea94cf17e492e8cf",
|
||||
"blk.1.ffn_gate.weight": "a7151bff00a545fa18b2c92dcd2a14572ccf9beb957a6c494f1374e8ebe174c9",
|
||||
"blk.1.ffn_norm.weight": "e197d71ea11b5276bc0167d2663b88089b3ff42b47ba91e85f6c5d95f6306435",
|
||||
"blk.1.ffn_up.weight": "57c182e0b14cccd1350d388f0c616991702e74281db54637451b70f4ccc24f9b",
|
||||
"blk.1.post_attention_norm.weight": "3c56f837168d784c2d8bac247c130bdca6610c095c8da4558c536ccad7605609",
|
||||
"blk.1.post_ffw_norm.weight": "d2a51d320fd01069dd7ccaa7082f16a7faeb671885607d7900b10a89c354d0fa",
|
||||
"blk.2.attn_k.weight": "bc103c818192de7ce36caaf89dc117be4df13fb902e0bd9a23c64edace5df9b6",
|
||||
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|
||||
}
|
|
@ -194,6 +194,8 @@ Refer to the section [above](#how-do-i-configure-ollama-server) for how to set e
|
|||
|
||||
If a different directory needs to be used, set the environment variable `OLLAMA_MODELS` to the chosen directory.
|
||||
|
||||
> Note: on Linux using the standard installer, the `ollama` user needs read and write access to the specified directory. To assign the directory to the `ollama` user run `sudo chown -R ollama:ollama <directory>`.
|
||||
|
||||
Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
|
||||
|
||||
## How can I use Ollama in Visual Studio Code?
|
||||
|
|
|
@ -10,7 +10,7 @@ Check your compute compatibility to see if your card is supported:
|
|||
| 9.0 | NVIDIA | `H100` |
|
||||
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080 SUPER` `RTX 4080` `RTX 4070 Ti SUPER` `RTX 4070 Ti` `RTX 4070 SUPER` `RTX 4070` `RTX 4060 Ti` `RTX 4060` |
|
||||
| | NVIDIA Professional | `L4` `L40` `RTX 6000` |
|
||||
| 8.6 | GeForce RTX 30xx | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060` |
|
||||
| 8.6 | GeForce RTX 30xx | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060` `RTX 3050 Ti` `RTX 3050` |
|
||||
| | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2` |
|
||||
| 8.0 | NVIDIA | `A100` `A30` |
|
||||
| 7.5 | GeForce GTX/RTX | `GTX 1650 Ti` `TITAN RTX` `RTX 2080 Ti` `RTX 2080` `RTX 2070` `RTX 2060` |
|
||||
|
|
112
docs/linux.md
112
docs/linux.md
|
@ -1,44 +1,59 @@
|
|||
# Ollama on Linux
|
||||
# Linux
|
||||
|
||||
## Install
|
||||
|
||||
Install Ollama running this one-liner:
|
||||
To install Ollama, run the following command:
|
||||
|
||||
>
|
||||
|
||||
```bash
|
||||
```shell
|
||||
curl -fsSL https://ollama.com/install.sh | sh
|
||||
```
|
||||
|
||||
## AMD Radeon GPU support
|
||||
|
||||
While AMD has contributed the `amdgpu` driver upstream to the official linux
|
||||
kernel source, the version is older and may not support all ROCm features. We
|
||||
recommend you install the latest driver from
|
||||
https://www.amd.com/en/support/linux-drivers for best support of your Radeon
|
||||
GPU.
|
||||
|
||||
## Manual install
|
||||
|
||||
### Download `ollama`
|
||||
Download and extract the package:
|
||||
|
||||
Download and extract the Linux package:
|
||||
|
||||
```bash
|
||||
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz | sudo tar zx -C /usr
|
||||
```shell
|
||||
curl -L https://ollama.com/download/ollama-linux-amd64.tgz -o ollama-linux-amd64.tgz
|
||||
sudo tar -C /usr -xzf ollama-linux-amd64.tgz
|
||||
```
|
||||
|
||||
If you have an AMD GPU, also download and extract the ROCm package into the same location
|
||||
```bash
|
||||
curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tgz | sudo tar zx -C /usr
|
||||
Start Ollama:
|
||||
|
||||
```shell
|
||||
ollama serve
|
||||
```
|
||||
|
||||
In another terminal, verify that Ollama is running:
|
||||
|
||||
```shell
|
||||
ollama -v
|
||||
```
|
||||
|
||||
### AMD GPU install
|
||||
|
||||
If you have an AMD GPU, also download and extract the additional ROCm package:
|
||||
|
||||
```shell
|
||||
curl -L https://ollama.com/download/ollama-linux-amd64-rocm.tgz -o ollama-linux-amd64-rocm.tgz
|
||||
sudo tar -C /usr -xzf ollama-linux-amd64-rocm.tgz
|
||||
```
|
||||
|
||||
### ARM64 install
|
||||
|
||||
Download and extract the ARM64-specific package:
|
||||
|
||||
```shell
|
||||
curl -L https://ollama.com/download/ollama-linux-arm64.tgz -o ollama-linux-arm64.tgz
|
||||
sudo tar -C /usr -xzf ollama-linux-arm64.tgz
|
||||
```
|
||||
|
||||
### Adding Ollama as a startup service (recommended)
|
||||
|
||||
Create a user for Ollama:
|
||||
Create a user and group for Ollama:
|
||||
|
||||
```bash
|
||||
sudo useradd -r -s /bin/false -m -d /usr/share/ollama ollama
|
||||
```shell
|
||||
sudo useradd -r -s /bin/false -U -m -d /usr/share/ollama ollama
|
||||
sudo usermod -a -G ollama $(whoami)
|
||||
```
|
||||
|
||||
Create a service file in `/etc/systemd/system/ollama.service`:
|
||||
|
@ -54,6 +69,7 @@ User=ollama
|
|||
Group=ollama
|
||||
Restart=always
|
||||
RestartSec=3
|
||||
Environment="PATH=$PATH"
|
||||
|
||||
[Install]
|
||||
WantedBy=default.target
|
||||
|
@ -61,46 +77,54 @@ WantedBy=default.target
|
|||
|
||||
Then start the service:
|
||||
|
||||
```bash
|
||||
```shell
|
||||
sudo systemctl daemon-reload
|
||||
sudo systemctl enable ollama
|
||||
```
|
||||
|
||||
### Install CUDA drivers (optional – for Nvidia GPUs)
|
||||
### Install CUDA drivers (optional)
|
||||
|
||||
[Download and install](https://developer.nvidia.com/cuda-downloads) CUDA.
|
||||
|
||||
Verify that the drivers are installed by running the following command, which should print details about your GPU:
|
||||
|
||||
```bash
|
||||
```shell
|
||||
nvidia-smi
|
||||
```
|
||||
|
||||
### Install ROCm (optional - for Radeon GPUs)
|
||||
[Download and Install](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html)
|
||||
### Install AMD ROCm drivers (optional)
|
||||
|
||||
Make sure to install ROCm v6
|
||||
[Download and Install](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html) ROCm v6.
|
||||
|
||||
### Start Ollama
|
||||
|
||||
Start Ollama using `systemd`:
|
||||
Start Ollama and verify it is running:
|
||||
|
||||
```bash
|
||||
```shell
|
||||
sudo systemctl start ollama
|
||||
sudo systemctl status ollama
|
||||
```
|
||||
|
||||
## Update
|
||||
> [!NOTE]
|
||||
> While AMD has contributed the `amdgpu` driver upstream to the official linux
|
||||
> kernel source, the version is older and may not support all ROCm features. We
|
||||
> recommend you install the latest driver from
|
||||
> https://www.amd.com/en/support/linux-drivers for best support of your Radeon
|
||||
> GPU.
|
||||
|
||||
Update ollama by running the install script again:
|
||||
## Updating
|
||||
|
||||
```bash
|
||||
Update Ollama by running the install script again:
|
||||
|
||||
```shell
|
||||
curl -fsSL https://ollama.com/install.sh | sh
|
||||
```
|
||||
|
||||
Or by downloading the ollama binary:
|
||||
Or by re-downloading Ollama:
|
||||
|
||||
```bash
|
||||
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz | sudo tar zx -C /usr
|
||||
```shell
|
||||
curl -L https://ollama.com/download/ollama-linux-amd64.tgz -o ollama-linux-amd64.tgz
|
||||
sudo tar -C /usr -xzf ollama-linux-amd64.tgz
|
||||
```
|
||||
|
||||
## Installing specific versions
|
||||
|
@ -109,15 +133,15 @@ Use `OLLAMA_VERSION` environment variable with the install script to install a s
|
|||
|
||||
For example:
|
||||
|
||||
```
|
||||
curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION=0.1.32 sh
|
||||
```shell
|
||||
curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION=0.3.9 sh
|
||||
```
|
||||
|
||||
## Viewing logs
|
||||
|
||||
To view logs of Ollama running as a startup service, run:
|
||||
|
||||
```bash
|
||||
```shell
|
||||
journalctl -e -u ollama
|
||||
```
|
||||
|
||||
|
@ -125,7 +149,7 @@ journalctl -e -u ollama
|
|||
|
||||
Remove the ollama service:
|
||||
|
||||
```bash
|
||||
```shell
|
||||
sudo systemctl stop ollama
|
||||
sudo systemctl disable ollama
|
||||
sudo rm /etc/systemd/system/ollama.service
|
||||
|
@ -133,13 +157,13 @@ sudo rm /etc/systemd/system/ollama.service
|
|||
|
||||
Remove the ollama binary from your bin directory (either `/usr/local/bin`, `/usr/bin`, or `/bin`):
|
||||
|
||||
```bash
|
||||
```shell
|
||||
sudo rm $(which ollama)
|
||||
```
|
||||
|
||||
Remove the downloaded models and Ollama service user and group:
|
||||
|
||||
```bash
|
||||
```shell
|
||||
sudo rm -r /usr/share/ollama
|
||||
sudo userdel ollama
|
||||
sudo groupdel ollama
|
||||
|
|
3
3