Tensor library for machine learning
Note that this project is under active development. \ Some of the development is currently happening in the llama.cpp and whisper.cpp repos
git clone https://github.com/ggerganov/ggml
cd ggml
# install python dependencies in a virtual environment
python3.10 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
# build the examples
mkdir build && cd build
cmake ..
cmake --build . --config Release -j 8
# run the GPT-2 small 117M model
../examples/gpt-2/download-ggml-model.sh 117M
./bin/gpt-2-backend -m models/gpt-2-117M/ggml-model.bin -p "This is an example"
For more information, checkout the corresponding programs in the examples folder.
# fix the path to point to your CUDA compiler
cmake -DGGML_CUDA=ON -DCMAKE_CUDA_COMPILER=/usr/local/cuda-12.1/bin/nvcc ..
cmake -DCMAKE_C_COMPILER="$(hipconfig -l)/clang" -DCMAKE_CXX_COMPILER="$(hipconfig -l)/clang++" -DGGML_HIPBLAS=ON
# linux
source /opt/intel/oneapi/setvars.sh
cmake -G "Ninja" -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON ..
# windows
"C:\Program Files (x86)\Intel\oneAPI\setvars.bat"
cmake -G "Ninja" -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DGGML_SYCL=ON ..
Download and unzip the NDK from this download page. Set the NDK_ROOT_PATH environment variable or provide the absolute path to the CMAKE_ANDROID_NDK in the command below.
cmake .. \
-DCMAKE_SYSTEM_NAME=Android \
-DCMAKE_SYSTEM_VERSION=33 \
-DCMAKE_ANDROID_ARCH_ABI=arm64-v8a \
-DCMAKE_ANDROID_NDK=$NDK_ROOT_PATH
-DCMAKE_ANDROID_STL_TYPE=c++_shared
# create directories
adb shell 'mkdir /data/local/tmp/bin'
adb shell 'mkdir /data/local/tmp/models'
# push the compiled binaries to the folder
adb push bin/* /data/local/tmp/bin/
# push the ggml library
adb push src/libggml.so /data/local/tmp/
# push model files
adb push models/gpt-2-117M/ggml-model.bin /data/local/tmp/models/
adb shell
cd /data/local/tmp
export LD_LIBRARY_PATH=/data/local/tmp
./bin/gpt-2-backend -m models/ggml-model.bin -p "this is an example"