ggml

Roadmap / Manifesto

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

Features

• Low-level cross-platform implementation
• Integer quantization support
• Broad hardware support
• Automatic differentiation
• ADAM and L-BFGS optimizers
• No third-party dependencies
• Zero memory allocations during runtime

Build

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

GPT inference (example)

# 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.

Using CUDA

# fix the path to point to your CUDA compiler
cmake -DGGML_CUDA=ON -DCMAKE_CUDA_COMPILER=/usr/local/cuda-12.1/bin/nvcc ..

Using hipBLAS

cmake -DCMAKE_C_COMPILER="$(hipconfig -l)/clang" -DCMAKE_CXX_COMPILER="$(hipconfig -l)/clang++" -DGGML_HIPBLAS=ON

Using SYCL

# 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 ..

Compiling for Android

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"

Resources

• Introduction to ggml
• The GGUF file format