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.