This repository contains our contribution to NLC2CMD Challenge
Install python dependencies:
pip install -r requirements.txt
Clone clai repository in the folder nearby
git clone https://github.com/IBM/clai.git
git checkout -t remotes/origin/nlc2cmd
Download preprocessed manpage data cmd_options_help.csv
To train the model(s) in the paper, run this command:
./train.sh <path to nl2bash-data.json> <path to manpage-data.json> <path to dev dir> <cmd_options_help.csv> <best clf model epoch> <best ctx model epoch>
for example
mkdir dev_dir
./train.sh nl2bash-data.json manpage-data.json dev_dir cmd_options_help.csv 4 6
To evaluate the model use tools from clai repository and submission_code folder.
You can download pretrained models here: pretrained models
Our model achieves the following performance on :
Model name | Accuracy | Energy (mW) |
---|---|---|
jb | 0.499 | 828.9 |
All content in this repository is licensed under the MIT license.