yedivanseven/slangmod repository overview

⁠slangmod

small language model

This is the companion docker image to the slangmod⁠ project, also available as a python package on PyPI⁠.

It has CUDA-enabled PyTorch⁠ already baked in, but you still need a host machine that

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

To use it, 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, refer to the project documentation⁠.