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T5-nl2cmd

T5-nl2cmd is a model that generates bash commands from natural language descriptions.

This repository contains the trained model, fine-tuned from Flan-T5 base.

Training data

Model

The model is fine-tuned from the Flan-T5 base model.

It has been trained on a single Nvidia L4 from Scaleway, for 4 hours and 4 epochs.

The model aims to generate bash commands from natural language descriptions.

Results

The results are evaluated on an 500 eval subset of the data cited above.

Metric Flan-T5 - Nl2cmd
exact 0.064
rouge 0.530054
bleu 0.177511
levenstein average 0.612479
levenstein median 0.608696

Examples :

Task Command
Count time, calls, and errors for each system call and report a summary on program exit slurmctl -c path/to/file
Search for a word in all the normal/regular files in the current folder find . -type f -exec grep -H
Start the daemon with verbose output coming from specific files in the bluetoothd or plugins source bluetoothd-start --verbose path/to/file
Find all directories under current directory and make them read, write, and executable for owner & group and remove read-write-execute permission for others find . -type d -exec chmod ug=
Set the verbosity level (error, warn, info, debug, or trace) svn -v verbosity
Show the configuration of a virtual machine, specifying its ID qm show vm_id
Import VPN configuration ipconfig import config
Find all the files ending with ".coffee" in the current folder and search for the words "re" in each line find . -name "*.coffee" -exec grep
Run a program from a file pstool --run path/to/file
Display details and metadata about a specified portable service image portablectl show-image path/to/image
Display all the files in the current folder excluding those which are in the path of ".git" find . -path '*.git' -prune -
Find all *.ogg files on the system ignoring the case find / -iname "*.ogg"
Print and recursively remove the alphabetically last directory in the current directory rmdir -rf

License :

Creative Commons cc-by-nc-sa 4.0

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Safetensors
Model size
248M params
Tensor type
F32
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Dataset used to train Edoigtrd/T5-nl2cmd