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- Connect to head.arcc.albany.edu via SSH (see: How-to: Connect via SSH (PuTTY, macOS terminal, X2Go)
Run the following commands, line by line. Make sure you change [lab_directory] to be your lab directory name.
Code Block language bash title Installing miniconda # download the install script wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh # execute the installer bash ~/miniconda.sh -b -p /network/rit/lab/[lab_directory]/miniconda # initialize the environment to your shell /network/rit/lab/[lab_directory]/miniconda/bin/conda init # If you are running bash, this is important cat ~/.bashrc >> ~/.bash_profile # finally, source your environment, you will only need to do this once source ~/.bash_profile
- Some helpful hints
- Do not install packages in your (base) environment (e.g.
conda activate base). It is best to create separate environments for different packages, or conda is at a risk of breaking (e.g.conda create -n tensorflow python=3) - Sharing conda across lab group members is possible, make sure the folder is g+rwx (
chmod -R g+rwx /network/rit/lab/[lab_directory]/miniconda) - Always check if conda has a software package available. There are many different channels, but researchers and software developers commonly publish to conda-forge (e.g.
conda install -c conda-forge ffmpeg) - Read the docs: https://conda.io/projects/conda/en/latest/user-guide/index.html
- Do not install packages in your (base) environment (e.g.
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