# Model factory with Python

> Model factory with Python - Learn how to use the Python threading library to build a model factory.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-06T18:17:09.582062+00:00` (UTC).

## Primary page

- [Model factory with Python](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-building-tuning/python-multi.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Model building and fine-tuning](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-building-tuning/index.html): Linked from this page.

## Documentation content

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/blob/main/advanced_ml_and_api_approaches/model-factory-with-python-native-multithreading/Model%20Factory%20with%20Python%20Multithreading.ipynb)

Model training in the DataRobot platform is an I/O-bound task that can be time consuming depending on the project configuration and the type of models to be trained.

Working under tough deadlines and needing to train tens or hundreds of projects (for example, at an SKU level) requires building model factories and leads to the mandatory requirement to significantly decrease training time.

This can be achieved on the base of a multithreaded approach and is demonstrated on the example of this AI Accelerator that leverages a Python multithreading library.