Build, simulate, and deploy federated learning at scale with the core Flower Framework. Easily federate existing machine learning projects with the Flower Python SDK.

On-device AI with optional Confidential Remote Compute.

Partition datasets for federated learning using framework agnostic, reproducible, and thoroughly tested flwr-datasets library.

Easily reproduce and build upon well-known research results with Flower Baselines.

Start easily by building on top of full Flower example projects covering a wide range of ML frameworks, platforms, and scenarios.

Under construction 🚧 Build and deploy federated learning clients at scale with Flower. Easily federate Android on-device training with the Flower Android SDK.

Under construction 🚧 Build and deploy federated learning clients at scale with Flower. Easily federate iOS on-device training with the Flower iOS SDK.

Under construction 🚧 Federate native on-device training with the Flower C++ SDK. Code example available, full docs coming soon.