This is a quick setup guide for different situations.
grafzahl requires a Python environment. By default,
grafzahl assumes you would like to use a miniconda-based
Python environment. It can be installed by using the provided
setup_grafzahl() function.
require(grafzahl)
setup_grafzahl(cuda = TRUE) # FALSE if you don't have CUDA compatible GPUs
## Use grafzahl right away, an example
model <- grafzahl(unciviltweets, model_type = "bertweet", model_name = "vinai/bertweet-base")There are other setup options.
In order to use grafzahl on Google Colab, please choose
the R-based Runtime (Runtime > Change Runtime Type > Runtime Type:
R). You might also want to choose a hardware accelerator, e.g. T4
GPU.
In this case, you need to enable the non-Conda mode,
i.e. use_nonconda(). By default, it will also install the
required Python packages.
If you don’t want to use any conda configuration on your local
machine, you can just install the Python packages
simpletransformers and emoji.
And then
Suppose you have installed a conda installation elsewhere. Please
note the base path of your conda installation.
Create a new conda environment with the default grafzahl environment name
conda env create -n grafzahl_condaenv_cuda
conda activate grafzahl_condaenv_cuda
conda install -n grafzahl_condaenv_cuda python pip pytorch pytorch-cuda cudatoolkit -c pytorch -c nvidia
python -m pip install simpletransformers emoji
conda deactivate
## Test the CUDA installation with
Rscript -e "grafzahl::detect_cuda()"There are two important options and envvars.
options("grafzahl.nonconda") controls whether to use the
non-conda mode. Envvar GRAFZAHL_MINICONDA_PATH controls the
base path of the conda installation. If it is "" (the
default), reticulate::miniconda_path() is used as the base
path.