Installing Concrete-ML using PyPi requires a Linux-based OS or macOS running on an x86 CPU. For Apple Silicon, Docker is the only currently supported option (see below).
Installing on Windows can be done using Docker or WSL. On WSL, Concrete-ML will work as long as the package is not installed in the /mnt/c/ directory, which corresponds to the host OS filesystem.
To install Concrete-ML from PyPi, run the following:
Concrete-ml can be installed using Docker by either pulling the latest image or a specific version:
The image can be used with Docker volumes, see the Docker documentation here.
The image can then be used via the following command:
This will launch a Concrete-ML enabled Jupyter server in Docker that can be accessed directly from a browser.
Alternatively, a shell can be lauched in Docker, with or without volumes: