Installation

Use pip

For users familiar with Python, we recommend installing with [pip][pip] within an isolated virtual environment. If not, you can use our pre-built docker images.

pip install ludwig

For large or long-running workloads, Ludwig can be run remotely in the cloud or on a private compute cluster using Ray.

Install additional packages

Optional Ludwig functionality is separated out into subpackages. Install what you need:

• ludwig[llm] for LLM dependencies.
• ludwig[serve] for serving dependencies.
• ludwig[viz] for visualization dependencies.
• ludwig[hyperopt] for hyperparameter optimization dependencies.
• ludwig[distributed] for distributed training on Ray using Dask.
• ludwig[explain] for prediction explanations.
• ludwig[tree] for LightGBM and tree-based models.
• ludwig[test] for running ludwig's integration and unit tests.
• ludwig[benchmarking] for Ludwig model benchmarking.
• ludwig[full] for the full set of dependencies.

Install from git

pip install git+https://github.com/ludwig-ai/ludwig.git

Install from source

git clone https://github.com/ludwig-ai/ludwig.git
cd ludwig
pip install -e .

Use devcontainers

Ludwig supports development on VSCode devcontainers. See Ludwig's devcontainer files.

Use pre-build docker images

See Ludiwg's docker docs.