T5-nl2bash Open Source Model - Instantly Transform Natural Language into Practical Bash Commands for Free

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T5 Nl2bash

Developed by Edoigtrd

A model fine-tuned based on Flan-T5, capable of converting natural language descriptions into Bash commands

Large Language Model

Transformers

Supports Multiple Languages#Natural Language to Bash #Command Line Generation #Terminal Automation

Downloads 162

Release Time : 4/4/2024

Model Overview

This model is specifically designed to convert natural language descriptions into corresponding Bash commands, helping users quickly generate command-line operations

Model Features

Natural Language to Command Conversion

Can understand natural language descriptions and generate corresponding Bash commands

Fine-tuned based on Flan-T5

Targeted fine-tuning on the Flan-T5 base model, optimizing command generation capabilities

Multi-scenario Applicability

Supports generating various common system operations and file processing commands

Model Capabilities

Natural Language Understanding

Bash Command Generation

System Operation Command Conversion

File Processing Command Generation

Use Cases

System Management

File Search

Generate file search commands based on descriptions

Example: 'find . -type f -exec grep -H'

Permission Settings

Generate directory permission setting commands based on descriptions

Example: 'find . -type d -exec chmod ug='

Development Tools

Log Level Settings

Generate log level setting commands based on descriptions

Example: 'svn -v log level'

🚀 T5-nl2bash

T5-nl2bash is a model designed to generate bash commands from natural language descriptions. This repository holds the trained model, which is fine - tuned from Flan - T5 base.

🚀 Quick Start

T5 - nl2bash simplifies the process of getting bash commands from natural language. You can utilize the trained model in this repository to generate bash commands based on your natural language input.

✨ Features

Generate bash commands from natural language descriptions.
Fine - tuned from the well - known Flan - T5 base model.

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

Basic Usage

The following table shows some examples of generating bash commands from natural language descriptions:

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`

📚 Documentation

Training data

Tldr.sh pages - tldr - dataset
nl2bash - nl2bash

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 - Nl2bash
exact	0.064
rouge	0.530054
bleu	0.177511
levenstein average	0.612479
levenstein median	0.608696

📄 License

[Creative Commons cc - by - nc - sa 4.0](https://creativecommons.org/licenses/by - nc - sa/4.0/)

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