Empower your machine
learning models with P2PFL

P2P Federated Learning (p2pfl) is a decentralized federated learning library, it allows creating basic
federated learning systems on p2p networks using gossip protocols.

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Easy to Use

Intuitive design makes it easy for anyone to use.


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Privacy and Security

Your data will never leave your device.


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Collaborative Environment

Work seamlessly with your team in a collaborative and decentralized environment.


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Scalability

Built for scalability and robustness to handle your growing needs.



PyTorch Setup Example

1from p2pfl.node import Node
2from p2pfl.learning.pytorch.mnist_examples.mnistfederated_dm import (MnistFederatedDM)
3from p2pfl.learning.pytorch.mnist_examples.models.mlp import MLP
4
5# Create nodes using PyTorch and MNIST dataset
6node1 = Node(
7  MLP(),
8  MnistFederatedDM(),
9)
10node2 = Node(
11  MLP(),
12  MnistFederatedDM(),
13)
14
15# Start nodes
16node1.start()
17node2.start()
18
19# Connect nodes
20node1.connect(node2.addr)
21
22# Start learning
23node.set_start_learning(rounds=2, epochs=1)

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