df54c723ae
The linux build now support parallel CPU builds to speed things up. This also exposes AMD GPU targets as an optional setting for advaced users who want to alter our default set.
137 lines
3.9 KiB
Markdown
137 lines
3.9 KiB
Markdown
# Development
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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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- gcc version 11.4.0 or higher
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```bash
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brew install go cmake gcc
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```
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Optionally enable debugging and more verbose logging:
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```bash
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# At build time
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export CGO_CFLAGS="-g"
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# At runtime
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export OLLAMA_DEBUG=1
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```
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Get the required libraries and build the native LLM code:
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```bash
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go generate ./...
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```
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Then build ollama:
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```bash
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go build .
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```
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Now you can run `ollama`:
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```bash
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./ollama
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```
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### Linux
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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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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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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.
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Then generate dependencies:
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```
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go generate ./...
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```
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Then build the binary:
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```
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go build .
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```
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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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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) developement packages first, as well as `cmake` and `golang`.
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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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the AMD GPU targets by setting AMDGPU_TARGETS (e.g. `AMDGPU_TARGETS="gfx1101;gfx1102"`)
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```
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go generate ./...
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```
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Then build the binary:
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```
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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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#### 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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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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you might use:
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```
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OLLAMA_CUSTOM_CPU_DEFS="-DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_F16C=on -DLLAMA_FMA=on" go generate ./...
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go build .
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```
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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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### Windows
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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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- 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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```powershell
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$env:CGO_ENABLED="1"
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go generate ./...
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go build .
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```
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#### Windows CUDA (NVIDIA)
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In addition to the common Windows development tools described above, install:
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- [NVIDIA CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html)
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