---
title: "Flower Datasets"
description: "Flower Datasets is a library that enables the creation of datasets for federated learning by partitioning centralized datasets to exhibit heterogeneity or using naturally partitioned datasets."
date: "2024-05-24"
author:
  name: "Adam Narożniak"
  position: "ML Engineer at Flower Labs"
  website: "https://discuss.flower.ai/u/adam.narozniak/summary"
related:
    - text: "Flower Datasets documentation"
      link: "https://flower.ai/docs/datasets/"
    - text: "Flower Datasets GitHub page"
      link: "https://github.com/adap/flower/tree/main/datasets"
---

Flower Datasets is a library that enables the creation of datasets for federated learning/analytics/evaluation by partitioning centralized datasets to exhibit heterogeneity or using naturally partitioned datasets. It was created by the Flower Labs team, which also created Flower - A Friendly Federated AI Framework.

The key features include:
* downloading datasets (HuggingFace `datasets` are used under the hood),
* partitioning (simulate different levels of heterogeneity by using one of the implemented partitioning schemes or create your own),
* creating centralized datasets (easily utilize centralized versions of the datasets),
* reproducibility (repeat the experiments with the same results),
* visualization (display the created partitions),
* ML agnostic (easy integration with all popular ML frameworks).


It is a supplementary library to Flower, with which it integrates easily.
