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P2PFL is a decentralized federated learning library that enables federated learning on peer-to-peer networks using gossip protocols, making collaborative AI model training possible without reliance on central servers.

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P2PFL - Federated Learning over P2P networks

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P2PFL is a general-purpose open-source library designed for the execution (simulated and in real environments) of Decentralized Federated Learning systems, specifically making use of P2P networks and the gossip protocols.

✨ Key Features

P2PFL offers a range of features designed to make decentralized federated learning accessible and efficient. For detailed information, please refer to our documentation.

Feature Description
πŸš€ Easy to Use Get started quickly with our intuitive API.
πŸ›‘οΈ Reliable Built for fault tolerance and resilience.
🌐 Scalable Leverages the power of peer-to-peer networks.
πŸ§ͺ Versatile Experiment in simulated or real-world environments.
πŸ”’ Private Prioritizes data privacy with decentralized architecture.
🧩 Flexible Designed to be easy to modify.
πŸ“ˆ Real-time Monitoring Manage and track experiment through P2PFL Web Services platform.
🧠 ML Frameworks Seamlessly integrate PyTorch, TensorFlow/Keras, and JAX models.
πŸ“‘ Communication Protocol Agnostic Choose the communication protocol that best suits your needs (e.g., gRPC).
πŸ”Œ Integrations Enhanced capabilities through integrations: Hugging Face Datasets, ML frameworks, communication protocols, and Ray for large-scale simulations.

πŸ“₯ Installation

πŸ‘¨πŸΌβ€πŸ’» For Users

pip install "p2pfl[torch]"

πŸ‘¨πŸΌβ€πŸ”§ For Developers

Open in GitHub Codespaces

🐍 Python (using Poetry)

git clone https://github.com/p2pfl/p2pfl.git
cd p2pfl
poetry install -E torch 

Note: Use the extras (-E) flag to install specific dependencies (e.g., -E torch). Use --no-dev to exclude development dependencies.

🐳 Docker

docker build -t p2pfl .
docker run -it --rm p2pfl bash

🎬 Quickstart

To start using P2PFL, follow our quickstart guide in the documentation.

πŸ“š Documentation & Resources

🀝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines. Please adhere to the project's code of conduct in CODE_OF_CONDUCT.md.

πŸ’¬ Community

Connect with us and stay updated:

⭐ Star History

A big thank you to the community for your interest in P2PFL! We appreciate your support and contributions.

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πŸ“œ License

GNU General Public License, Version 3.0

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P2PFL is a decentralized federated learning library that enables federated learning on peer-to-peer networks using gossip protocols, making collaborative AI model training possible without reliance on central servers.

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