How to permanently install Rapids on Google colab?

Is there a way to install Rapids permanently on Google colab? I tried many solutions given on StackOverflow and other websites but nothing is working. This is a very big library and it is very frustrating to download this every time I want to work on colab.

I tried this code from Rapids but it is also not working. When I close colab and start again later, I get ModuleNotFoundError: No module named 'cudf'.

# Install RAPIDS!git clone https://github.com/rapidsai/rapidsai-csp-utils.git!bash rapidsai-csp-utils/colab/rapids-colab.sh stableimport sys, os, shutilsys.path.append('/usr/local/lib/python3.7/site-packages/')os.environ['NUMBAPRO_NVVM'] = '/usr/local/cuda/nvvm/lib64/libnvvm.so'os.environ['NUMBAPRO_LIBDEVICE'] = '/usr/local/cuda/nvvm/libdevice/'os.environ["CONDA_PREFIX"] = "/usr/local"for so in ['cudf', 'rmm', 'nccl', 'cuml', 'cugraph', 'xgboost', 'cuspatial']:  fn = 'lib'+so+'.so'  source_fn = '/usr/local/lib/'+fn  dest_fn = '/usr/lib/'+fn  if os.path.exists(source_fn):    print(f'Copying {source_fn} to {dest_fn}')    shutil.copyfile(source_fn, dest_fn)# fix for BlazingSQL import issue# ImportError: /usr/lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.26' not found (required by /usr/local/lib/python3.7/site-packages/../../libblazingsql-engine.so)if not os.path.exists('/usr/lib64'):    os.makedirs('/usr/lib64')for so_file in os.listdir('/usr/local/lib'):  if 'libstdc' in so_file:    shutil.copyfile('/usr/local/lib/'+so_file, '/usr/lib64/'+so_file)    shutil.copyfile('/usr/local/lib/'+so_file, '/usr/lib/x86_64-linux-gnu/'+so_file)

A solution has been suggested but which uses pip to install libraries - How do I install a library permanently in Colab? but Rapids can't be installed using pip. It can only be installed using Conda. This is the code to install it.

conda create -n rapids-0.19 -c rapidsai -c nvidia -c conda-forge \    rapids-blazing=0.19 python=3.7 cudatoolkit=11.0

I tried to include the google drive path(nb_path) to this code using the --prefix flag as suggested by the above link !pip install --target=$nb_path jdc but I am getting a syntax error.

Can anyone tell me how to set this nb_path to the conda create code above?