update go to 1.22 in other places (#2975)
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Jeffrey Morgan
GitHub
parent
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d481fb3cc8
3 changed files with 20 additions and 21 deletions
14
.github/workflows/test.yaml
vendored
14
.github/workflows/test.yaml
vendored
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@ -21,7 +21,7 @@ jobs:
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- uses: actions/checkout@v4
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- uses: actions/setup-go@v5
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with:
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go-version: '1.21'
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go-version: '1.22'
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cache: true
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- run: go get ./...
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- run: go generate -x ./...
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@ -46,7 +46,7 @@ jobs:
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- uses: actions/checkout@v4
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- uses: actions/setup-go@v4
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with:
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go-version: '1.21'
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go-version: '1.22'
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cache: true
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- run: go get ./...
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- run: |
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@ -76,7 +76,7 @@ jobs:
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- uses: actions/checkout@v4
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- uses: actions/setup-go@v4
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with:
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go-version: '1.21'
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go-version: '1.22'
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cache: true
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- run: go get ./...
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- run: |
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@ -103,14 +103,14 @@ jobs:
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runs-on: ${{ matrix.os }}
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env:
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GOARCH: ${{ matrix.arch }}
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CGO_ENABLED: "1"
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CGO_ENABLED: '1'
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steps:
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- uses: actions/checkout@v4
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with:
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submodules: recursive
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- uses: actions/setup-go@v5
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with:
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go-version: '1.21'
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go-version: '1.22'
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cache: false
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- run: |
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mkdir -p llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/
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@ -140,14 +140,14 @@ jobs:
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runs-on: ${{ matrix.os }}
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env:
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GOARCH: ${{ matrix.arch }}
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CGO_ENABLED: "1"
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CGO_ENABLED: '1'
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steps:
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- uses: actions/checkout@v4
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with:
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submodules: recursive
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- uses: actions/setup-go@v5
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with:
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go-version: '1.21'
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go-version: '1.22'
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cache: true
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- run: go get
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- uses: actions/download-artifact@v4
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@ -1,4 +1,4 @@
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ARG GOLANG_VERSION=1.21.3
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ARG GOLANG_VERSION=1.22.1
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ARG CMAKE_VERSION=3.22.1
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ARG CUDA_VERSION=11.3.1
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@ -3,7 +3,7 @@
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Install required tools:
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- cmake version 3.24 or higher
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- go version 1.21 or higher
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- go version 1.22 or higher
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- gcc version 11.4.0 or higher
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```bash
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@ -42,15 +42,15 @@ Now you can run `ollama`:
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#### Linux CUDA (NVIDIA)
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*Your operating system distribution may already have packages for NVIDIA CUDA. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!*
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_Your operating system distribution may already have packages for NVIDIA CUDA. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
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Install `cmake` and `golang` as well as [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
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development and runtime packages.
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development and runtime packages.
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Typically the build scripts will auto-detect CUDA, however, if your Linux distro
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or installation approach uses unusual paths, you can specify the location by
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specifying an environment variable `CUDA_LIB_DIR` to the location of the shared
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libraries, and `CUDACXX` to the location of the nvcc compiler. You can customize
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libraries, and `CUDACXX` to the location of the nvcc compiler. You can customize
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set set of target CUDA architectues by setting `CMAKE_CUDA_ARCHITECTURES` (e.g. "50;60;70")
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Then generate dependencies:
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@ -67,7 +67,7 @@ go build .
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#### Linux ROCm (AMD)
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*Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!*
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_Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
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Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) development packages first, as well as `cmake` and `golang`.
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@ -75,7 +75,7 @@ Typically the build scripts will auto-detect ROCm, however, if your Linux distro
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or installation approach uses unusual paths, you can specify the location by
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specifying an environment variable `ROCM_PATH` to the location of the ROCm
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install (typically `/opt/rocm`), and `CLBlast_DIR` to the location of the
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CLBlast install (typically `/usr/lib/cmake/CLBlast`). You can also customize
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CLBlast install (typically `/usr/lib/cmake/CLBlast`). You can also customize
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the AMD GPU targets by setting AMDGPU_TARGETS (e.g. `AMDGPU_TARGETS="gfx1101;gfx1102"`)
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```
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@ -88,17 +88,17 @@ Then build the binary:
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go build .
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```
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ROCm requires elevated privileges to access the GPU at runtime. On most distros you can add your user account to the `render` group, or run as root.
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ROCm requires elevated privileges to access the GPU at runtime. On most distros you can add your user account to the `render` group, or run as root.
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#### Advanced CPU Settings
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By default, running `go generate ./...` will compile a few different variations
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of the LLM library based on common CPU families and vector math capabilities,
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including a lowest-common-denominator which should run on almost any 64 bit CPU
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somewhat slowly. At runtime, Ollama will auto-detect the optimal variation to
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load. If you would like to build a CPU-based build customized for your
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somewhat slowly. At runtime, Ollama will auto-detect the optimal variation to
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load. If you would like to build a CPU-based build customized for your
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processor, you can set `OLLAMA_CUSTOM_CPU_DEFS` to the llama.cpp flags you would
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like to use. For example, to compile an optimized binary for an Intel i9-9880H,
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like to use. For example, to compile an optimized binary for an Intel i9-9880H,
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you might use:
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```
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@ -108,8 +108,7 @@ go build .
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#### Containerized Linux Build
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If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
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If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
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### Windows
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@ -118,7 +117,7 @@ Note: The windows build for Ollama is still under development.
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Install required tools:
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- MSVC toolchain - C/C++ and cmake as minimal requirements
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- go version 1.21 or higher
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- go version 1.22 or higher
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- MinGW (pick one variant) with GCC.
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- <https://www.mingw-w64.org/>
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- <https://www.msys2.org/>
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