mirror of https://github.com/skygpu/skynet.git
Guillermo Rodriguez
3622c8ea11
Improve readme Improve dockerization as ipfs cli exec runs not needed anymore Fix pyproject toml for gpu workers Add more sections on example config Drop and siomplify many cli commands, try to use config.ini for everything now Use more dynamic imports on cli to speed up startup Improve model pipelines to allow low mem cards to run big models Add upscaler download to `skynet download` cmd |
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| docker | ||
| skynet | ||
| tests | ||
| .dockerignore | ||
| .gitignore | ||
| LICENSE | ||
| README.md | ||
| build_docker.sh | ||
| launch_ipfs.sh | ||
| poetry.lock | ||
| poetry.toml | ||
| pyproject.toml | ||
| pytest.ini | ||
| skynet.ini.example | ||
README.md
skynet
decentralized compute platform
To launch a worker:
native install
system dependencies: - cuda 11.8 - llvm 10 - python 3.10+ - docker (for ipfs node)
# create and edit config from template
cp skynet.ini.example skynet.ini
# install poetry package manager
curl -sSL https://install.python-poetry.org | python3 -
# install
poetry install
# enable environment
poetry shell
# test you can run this command
skynet --help
# launch ipfs node
skynet run ipfs
# to launch worker
skynet run dgpu
dockerized install
system dependencies: - docker with gpu enabled
# pull runtime container
docker pull guilledk/skynet:runtime-cuda
# or build it (takes a bit of time)
./build_docker.sh
# launch simple ipfs node
./launch_ipfs.sh
# run worker
docker run \
-it \
--rm \
--gpus all \
--network host \
--mount type=bind,source="$(pwd)",target=/root/target \
guilledk/skynet:runtime-cuda \
skynet run dgpu