installation

package

Create and activate a new virtual environment running at least python 3.12.
The easiest way of installing slangmod is from the python package index PyPI, where it is hosted. Simply type
```
pip install slangmod
```
or treat it like any other python package in your dependency management.
While it is, in principle, possible to run slangmod on the CPU, this is only intended for debugging purposes. To get any results in finite time, you also need a decent graphics card, and you must have a working installation of PyTorch to make good use of it. Because there is no way of knowing which version of CUDA (or ROC) you have installed on your machine and how you installed it, PyTorch it is not an explicit dependency of slangmod. You will have to install it yourself, e.g., following these instructions. If you are using pipenv for dependency management, you can also have a look at the Pipfile in the root of the slangmod repository and taylor it to your needs. Personally, I go
```
pipenv sync --categories=cpu
```
for a CPU-only installation of PyTorch (for debugging only) and
```
pipenv sync --categories=cuda
```
if I want GPU support.
Finally, with the virtual environment you just created active, open a console and type
```
slangmod -h
```
to check that everything works.

docker

A docker image with GPU-enabled PyTorch and all other dependencies inside is available on the Docker Hub.

docker pull yedivanseven/slangmod

To use it, you must have a host machine that

has an NVIDIA GPU,
has the drivers for it installed, and
exposes it via the container toolkit.

Change into a working directory, i.e., one where slangmod will read its config file slangmod.toml from and where it will save outputs to, and mount this directory to the path /workdir inside the container when you run it.

docker run --rm --gpus all -v ./:/workdir yedivanseven/slangmod

This will invoke slangmod -h. If all went well, the “device” entry under the section “data” should read “cuda”.

In the event that you still want to clean your raw text with the help of slangmod, you will also have to mount the folder with those dirty files when your start a docker container.

docker run --rm --gpus all -v ./:/workdir -v /path/to/raw/docs:/raw yedivanseven/slangmod clean ...

For all other command-line options and to find out about this config TOML file, read on …