Installation#

Cloud Environments#

Launch into a JupyterLab environment on

Local Environments#

Start by cloning this repo-url

git clone https://github.com/Clay-foundation/model
cd model

Then we recommend using mamba to install the dependencies. A virtual environment will also be created with Python and JupyterLab installed.

mamba env create --file environment.yml

Note

The command above will only work for Linux devices with CUDA GPUs. For installation on macOS devices (either Intel or ARM chips), follow the ‘Advanced’ section below.

Activate the virtual environment first.

mamba activate claymodel

Finally, double-check that the libraries have been installed.

mamba list

Advanced#

This is for those who want full reproducibility of the virtual environment. Create a virtual environment with just Python and conda-lock installed first.

mamba create --name claymodel python=3.11 conda-lock=2.5.6
mamba activate claymodel

Installing/Updating a virtual environment from a lockile. Use this to sync your dependencies to the exact versions in the conda-lock.yml file.

conda-lock install --mamba --name claymodel conda-lock.yml

See also https://conda.github.io/conda-lock/output/#unified-lockfile for more usage details.

Note

To generate a unified conda-lock.yml file based on the dependency specification in environment.yml, run:

conda-lock lock --mamba --file environment.yml --with-cuda=12.0

Use this only when creating a new conda-lock.yml file or refreshing an existing one.