ggml

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/ggml-org/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.

Resources

• Introduction to ggml
• The GGUF file format