Flower Framework Documentation

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

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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.

Tutorials

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

Tutorial

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

We also made video tutorials for PyTorch:

And TensorFlow:

How-to guides

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

How-to guides

Legacy example guides

Explanations

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

Explanations

References

Information-oriented API reference and other reference material.

flwr

Flower main package.

Reference docs

Contributor docs

The Flower community welcomes contributions. The following docs are intended to help along the way.

Contributor tutorials

Contributor how-to guides

Contributor explanations

Contributor references