Data version control (DVC) is open-source, Git version control for machine learning projects. Benefits include:
- Reproducible and shareable machine learning models and pipelines
- Git version large datasets and models without Git-LFS
- Git diffs for model and data metrics across commits, tags and branches
The iterative/setup-dvc action is a JavaScript action that sets up DVC in your workflow.
This action can be run on ubuntu-latest
, macos-latest
, windows-latest
.
When running on windows-latest
, Python 3 is a dependency that should be setup first (and there's an action for that).
Basic usage:
steps:
- uses: actions/checkout@v2
- uses: iterative/setup-dvc@v1
Windows:
steps:
- uses: actions/checkout@v2
- uses: actions/setup-python@v2
with:
python-version: '3.x'
- uses: iterative/setup-dvc@v1
A specific version can be pinned to your workflow using the version
argument.
steps:
- uses: actions/checkout@v2
- uses: iterative/setup-dvc@v1
with:
version: '1.0.1'
The following inputs are supported.
version
- (optional) The version of DVC to install. A value oflatest
will install the latest version of DVC. Defaults tolatest
.
Setup DVC has no outputs.