Flower Documentation#

Welcome to Flower’s documentation. Flower is a friendly federated learning framework.

Join the Flower Community#

The Flower Community is growing quickly - we’re a friendly group of researchers, engineers, students, professionals, academics, and other enthusiasts.

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Flower Framework#

The user guide is targeted at researchers and developers who want to use Flower to bring existing machine learning workloads into a federated setting. One of Flower’s design goals was to make this simple. Read on to learn more.


A learning-oriented series of federated learning tutorials, the best place to start.

QUICKSTART TUTORIALS: PyTorch | TensorFlow | 🤗 Transformers | JAX | Pandas | fastai | PyTorch Lightning | MXNet | scikit-learn | XGBoost

How-to guides#

Problem-oriented how-to guides show step-by-step how to achieve a specific goal.


Understanding-oriented concept guides explain and discuss key topics and underlying ideas behind Flower and collaborative AI.


Information-oriented API reference and other reference material.

API reference

Flower Baselines#

Flower Baselines are a collection of organised scripts used to reproduce results from well-known publications or benchmarks. You can check which baselines already exist and/or contribute your own baseline.

Contributor Guide#

The Flower authors welcome external contributions. The following guides are intended to help along the way.