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Flower Examples 1.19.0
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Flower Examples 1.19.0

Quickstart

  • Flower Clients in C++ (under development)
  • Federated Learning with fastai and Flower (Quickstart Example)
  • Federated Learning with HuggingFace Transformers and Flower (Quickstart Example)
  • Federated Learning with JAX and Flower (Quickstart Example)
  • Federated Learning with Hugging Face LeRobot and Flower (Quickstart Example)
  • Federated Learning with MLX and Flower (Quickstart Example)
  • Federated Learning with MONAI and Flower (Quickstart Example)
  • Federated Learning with Pandas and Flower (Quickstart Example)
  • Federated Learning with PyTorch and Flower (Quickstart Example)
  • Federated Learning with PyTorch Lightning and Flower (Quickstart Example)
  • Install dependencies and project
  • Federated Learning with scikit-learn and Flower (Quickstart Example)
  • Federated Learning with Tensorflow/Keras and Flower (Quickstart Example)
  • Federated Learning with XGBoost and Flower (Quickstart Example)

Advanced

  • Federated Learning with PyTorch and Flower (Advanced Example)
  • Federated Learning with TensorFlow/Keras and Flower (Advanced Example)
  • Flower Federations with Authentication 🧪
  • Secure aggregation with Flower (the SecAgg+ protocol)
  • Vertical Federated Learning with Flower
  • Federated Learning with XGBoost and Flower (Comprehensive Example)

Others

  • Flower Android Example (TensorFlowLite)
  • Flower Android Client Example with Kotlin and TensorFlow Lite 2022
  • app-pytorch: A Flower / PyTorch app
  • Custom Metrics for Federated Learning with TensorFlow and Flower
  • Using custom mods 🧪
  • Setting up your Embedded Device
  • Federated Survival Analysis with Flower and KaplanMeierFitter
  • Federated Retrieval Augmented Generation (FedRAG)
  • Flower Example on MNIST with Differential Privacy and Secure Aggregation
  • Flower Example on Adult Census Income Tabular Dataset
  • 30-minute tutorial running Flower simulation with PyTorch
  • Flower Simulation Step-by-Step
  • Leveraging Flower and Docker for Device Heterogeneity Management in Federated Learning
  • FlowerTune LLM: Federated LLM Fine-tuning with Flower
  • Federated Finetuning of a Vision Transformer with Flower
  • FLiOS - A Flower SDK for iOS Devices with Example
  • Training with Sample-Level Differential Privacy using Opacus Privacy Engine
  • Federated Variational Autoencoder with PyTorch and Flower
  • PyTorch: From Centralized To Federated
  • Flower Logistic Regression Example using scikit-learn and Flower (Quickstart Example)
  • Training with Sample-Level Differential Privacy using TensorFlow-Privacy Engine
  • On-device Federated Finetuning for Speech Classification
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