Skip to main content

A tool for initializing AI model training repositories

Project description

modinit

modinit is a Python package that helps you quickly scaffold AI model training repositories with a standardized, best-practice structure. It saves you time and ensures consistency across your machine learning projects.

Why use modinit?

  • Instant project setup: Get started with a ready-to-use directory structure in seconds.
  • Best practices built-in: Follows common conventions for organizing data, code, configs, and tests.
  • Docstring templates: All generated Python files include helpful docstrings.
  • Easy to use: Simple command-line interface.

Demo

modinit demo

Installation

pip install modinit

Usage

To create a new project, run:

modinit my-project

This will generate a new directory called my-project with a recommended structure for AI/ML projects.

Example

Below is a real example of using modinit to create a project called voice-rumba:

$ pip install modinit
$ modinit voice-rumba
Successfully created project: voice-rumba
To get started, navigate to the project directory:
  cd voice-rumba

The generated structure looks like this:

voice-rumba/
├── README.md
├── .gitignore
├── configs/
│   └── config.yaml
├── data/
│   ├── raw/
│   ├── processed/
│   └── interim/
├── main.py
├── notebooks/
│   └── prototype.ipynb
├── requirements.txt
├── src/
│   ├── __init__.py
│   ├── data.py
│   ├── evaluate.py
│   ├── model.py
│   ├── train.py
│   └── utils.py
└── tests/
    ├── __init__.py
    ├── test_data.py
    ├── test_model.py
    └── test_train.py

Features

  • Creates a well-structured project directory for AI model training
  • Follows best practices for machine learning project organization
  • Includes helpful docstrings in all generated files
  • Simple command-line interface

Development

To contribute to this project:

  1. Clone the repository
  2. Create a virtual environment
  3. Install development dependencies: pip install -e ".[dev]"
  4. Make your changes
  5. Run tests: pytest

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

modinit-0.1.1.tar.gz (14.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

modinit-0.1.1-py3-none-any.whl (19.7 kB view details)

Uploaded Python 3

File details

Details for the file modinit-0.1.1.tar.gz.

File metadata

  • Download URL: modinit-0.1.1.tar.gz
  • Upload date:
  • Size: 14.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.10

File hashes

Hashes for modinit-0.1.1.tar.gz
Algorithm Hash digest
SHA256 1bd46f2b2e7f522a028088de8ba6cee805d6a5dc06f5a6486805157ab191cf16
MD5 effb5a561f6c977dd242dcef8add8997
BLAKE2b-256 48bca4cf05768051c38abf1b9aa2af6a3a3749b6534422d3e49711cb271cd58b

See more details on using hashes here.

File details

Details for the file modinit-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: modinit-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 19.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.10

File hashes

Hashes for modinit-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a87ef62c8cebe96dbb548f5f0413d569be79afd3a0d97234cd64527fc5a3b4a3
MD5 ee545b34670b01768a32ff7bf813bad9
BLAKE2b-256 e71e80a07d5d39a3a15a32c96ca67d968f78b5a3c920e8c6f2ea4e2c4613b85a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page