GPU & Compute

ML/DL Project Template

A PyTorch Lightning template for deep learning projects with best practices.

Status
UnmaintainedGitHub repository has been archived.
Last checked
Checked · Oct 16, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

This project template provides a structured and efficient way to start new deep learning projects using PyTorch Lightning, ensuring adherence to best practices in model training and evaluation.

This template offers a standardized, best-practice approach to deep learning projects using PyTorch Lightning, making it easier for developers to start new projects without reinventing the wheel.

When it fits — and when it doesn’t

A good fit for

  • Teams starting new PyTorch projects who want to follow best practices

  • Developers looking for a structured approach to deep learning project setup

  • Educators teaching deep learning courses who need a consistent template

Look elsewhere if

  • Projects requiring real-time model inference (this is more of a development tool)

  • Teams already deeply invested in another framework's project structure and conventions

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Steep learning curve for non-Python developers

    The project template is deeply integrated with Python-specific patterns and idioms, which may be challenging for developers unfamiliar with Python.

  2. 02

    Limited language support restricts multi-language teams

    As the primary language is Python, there is no official support for other languages like Java or C++, limiting its utility in polyglot development environments.

  3. 03

    Documentation lacks depth on advanced use cases

    While basic usage is covered, detailed documentation on integrating custom PyTorch Lightning modules and handling edge cases is sparse.

  4. 04

    Performance bottlenecks in large-scale projects

    In larger datasets or more complex models, the default configurations may lead to performance issues that require manual optimization.

What it does well

  • Structured project layout for deep learning projects

  • Integration with PyTorch and PyTorch Lightning

  • Best practices for model training, evaluation, and testing

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

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Set up ML/DL Project Template

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
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