FLEXible

FLEXible (Federated Learning Experiments) is a Python framework offering tools to simulate FL with deep learning. It includes built-in datasets (MNIST, CIFAR10, Shakespeare), supports TensorFlow/PyTorch, and has extensions for adversarial attacks, anomaly detection, and decision trees.

Features

Comes with federated datasets like MNIST, CIFAR10, Shakespeare
Compatible with PyTorch and TensorFlow models
Extensions for adversarial testing (FLEX-Clash)
Supports anomaly detection (flex-anomalies)
Decision-tree FL tools (flex-trees)
Blockchain simulation support (FLEX-block)

Project Samples

Project Activity

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License

Affero GNU Public License

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FLEXible Web Site

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Federated Learning Frameworks

Registered

2025-07-15

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