Command line tool for improving typing speed and accuracy. The main goal is
to help programmers practise programming languages.
pip install --upgrade mltype
- Using neural networks to generate text. One can use
pretrained networks (see below) or train new ones from scratch.
- Alternatively, one can read text from a file or provide it manually
- Dead simple (implemented in
- Basic statistics – WPM and accuracy
- Setting target speed
- Playing against past performances
- Detailed documentation: https://mltype.readthedocs.io/en/latest/index.html.
- GIF examples: https://mltype.readthedocs.io/en/latest/source/examples.html.
The entrypoint is
$ mlt Usage: mlt [OPTIONS] COMMAND [ARGS]... Tool for improving typing speed and accuracy Options: --help Show this message and exit. Commands: file Type text from a file ls List all language models random Sample characters randomly from a vocabulary raw Provide text manually replay Compete against a past performance sample Sample text from a language train Train a language
See below a list of pretrained models. They are stored on a google drive
and one needs to download the entire archive.
Once you download the file, you will need to place it in
Note that if the folder does not exist you will have to create it. The file name
can be changed to whatevery you like. This name will then be used to
refer to the model.
To verify that the model was downloaded succesfully, try to sample from it.
Note that this might take 20+ seconds the first time around.
This project is very much motivated by the The Unreasonable Effectiveness of
Recurrent Neural Networks by Andrej Karpathy.