Flower Examples Documentation ----------------------------- Welcome to Flower Examples' documentation. `Flower `_ is a friendly federated learning framework. Join the Flower Community ------------------------- The Flower Community is growing quickly - we're a friendly group of researchers, engineers, students, professionals, academics, and other enthusiasts. .. button-link:: https://flower.ai/join-slack :color: primary :shadow: Join us on Slack Quickstart Examples ------------------- Flower Quickstart Examples are a collection of demo projects that show how you can use Flower in combination with other existing frameworks or technologies. .. list-table:: :widths: 50 15 15 15 :header-rows: 1 * - Title - Framework - Dataset - Tags * - `Flower Clients in C++ (under development) `_ - `C++ `_ - Synthetic - quickstart, linear regression, tabular * - `Federated Learning with fastai and Flower (Quickstart Example) `_ - `fastai `_ - `MNIST `_ - quickstart, vision * - `Federated Learning with HuggingFace Transformers and Flower (Quickstart Example) `_ - `transformers `_ - `IMDB `_ - quickstart, llm, nlp, sentiment * - `JAX: From Centralized To Federated `_ - `JAX `_ - Synthetic - quickstart, linear regression * - `Flower Example using TensorFlow/Keras + MLCube `_ - `mlcube `_, `tensorflow `_, `Keras `_ - `MNIST `_ - quickstart, vision, deployment * - `Federated Learning with MLX and Flower (Quickstart Example) `_ - `MLX `_ - `MNIST `_ - quickstart, vision * - `Federated Learning with MONAI and Flower (Quickstart Example) `_ - `MONAI `_ - `MedNIST `_ - quickstart, medical, vision * - `Federated Learning with Pandas and Flower (Quickstart Example) `_ - `pandas `_ - `Iris `_ - quickstart, tabular, federated analytics * - `Federated Learning with PyTorch and Flower (Quickstart Example) `_ - `torch `_, `torchvision `_ - `CIFAR-10 `_ - quickstart, vision, fds * - `Federated Learning with PyTorch Lightning and Flower (Quickstart Example) `_ - `lightning `_ - `MNIST `_ - quickstart, vision, fds * - `Federated Learning with scikit-learn and Flower (Quickstart Example) `_ - `scikit-learn `_ - `Iris `_ - quickstart, tabular, fds * - `Flower TabNet Example using TensorFlow `_ - `tabnet `_ - `Iris `_ - quickstart, tabular * - `Federated Learning with Tensorflow/Keras and Flower (Quickstart Example) `_ - `tensorflow `_ - `CIFAR-10 `_ - quickstart, vision, fds * - `Federated Learning with XGBoost and Flower (Quickstart Example) `_ - `xgboost `_ - `HIGGS `_ - quickstart, classification, tabular Advanced Examples ----------------- Advanced Examples are mostly for users that are both familiar with Federated Learning but also somewhat familiar with Flower's main features. .. list-table:: :widths: 50 15 15 15 :header-rows: 1 * - Title - Framework - Dataset - Tags * - `Federated Learning with PyTorch and Flower (Advanced Example) `_ - `torch `_, `torchvision `_ - Fashion-MNIST - advanced, vision, fds, wandb * - `Advanced Flower Example (TensorFlow/Keras) `_ - `tensorflow `_, `Keras `_ - `CIFAR-10 `_ - advanced, vision, fds * - `Flower Authentication with PyTorch 🧪 `_ - `torch `_, `torchvision `_ - `CIFAR-10 `_ - advanced, vision, fds * - `Secure aggregation with Flower (the SecAgg+ protocol) `_ - `torch `_, `torchvision `_ - `CIFAR-10 `_ - advanced, secure_aggregation, privacy * - `Vertical Federated Learning with Flower `_ - `torch `_, `pandas `_, `scikit-learn `_ - `Titanic `_ - vertical, tabular, advanced * - `Federated Learning with XGBoost and Flower (Comprehensive Example) `_ - `xgboost `_ - `HIGGS `_ - advanced, classification, tabular Other Examples -------------- Flower Examples are a collection of example projects written with Flower that explore different domains and features. You can check which examples already exist and/or contribute your own example. .. list-table:: :widths: 50 15 15 15 :header-rows: 1 * - Title - Framework - Dataset - Tags * - `Flower Android Example (TensorFlowLite) `_ - `Android `_, `Java `_, `TensorFlowLite `_ - `CIFAR-10 `_ - mobile, vision, sdk * - `Flower Android Client Example with Kotlin and TensorFlow Lite 2022 `_ - `Android `_, `Kotlin `_, `TensorFlowLite `_ - `CIFAR-10 `_ - mobile, vision, sdk * - `Flower App (PyTorch) 🧪 `_ - `torch `_, `torchvision `_ - `CIFAR-10 `_ - basic, vision, fds * - `Custom Metrics for Federated Learning with TensorFlow and Flower `_ - `tensorflow `_, `scikit-learn `_ - `CIFAR-10 `_ - basic, vision, fds * - `Using custom mods 🧪 `_ - `wandb `_, `tensorboard `_ - `CIFAR-10 `_ - mods, monitoring, app * - `Federated Learning on Embedded Devices with Flower `_ - `torch `_, `tensorflow `_ - `CIFAR-10 `_, `MNIST `_ - basic, vision, fds * - `Federated Survival Analysis with Flower and KaplanMeierFitter `_ - `lifelines `_ - `Waltons `_ - estimator, medical * - `Flower Example on MNIST with Differential Privacy and Secure Aggregation `_ - `torch `_, `torchvision `_ - `MNIST `_ - DP, SecAgg, vision, fds * - `Flower Example on Adult Census Income Tabular Dataset `_ - `scikit-learn `_, `torch `_ - `Adult Census Income `_ - basic, tabular, fds * - `30-minute tutorial running Flower simulation with PyTorch `_ - `torch `_ - `CIFAR-10 `_ - colab, vision, simulation * - `Flower Simulation Step-by-Step `_ - `torch `_ - `MNIST `_ - basic, vision, simulation * - `Leveraging Flower and Docker for Device Heterogeneity Management in Federated Learning `_ - `Docker `_, `tensorflow `_ - `CIFAR-10 `_ - deployment, vision, tutorial * - `FlowerTune LLM: Federated LLM Fine-tuning with Flower `_ - `PEFT `_, `torch `_ - `Alpaca-GPT4 `_ - llm, nlp, LLama * - `Federated Finetuning of a Vision Transformer with Flower `_ - `torch `_, `torchvision `_ - `Oxford Flower-102 `_ - finetuning, vision, fds * - `FLiOS - A Flower SDK for iOS Devices with Example `_ - `Swift `_ - `MNIST `_ - mobile, vision, sdk * - `Training with Sample-Level Differential Privacy using Opacus Privacy Engine `_ - `opacus `_, `torch `_ - `CIFAR-10 `_ - DP, DP-SGD, basic, vision, fds, privacy * - `Federated Variational Autoencoder with PyTorch and Flower `_ - `torch `_, `torchvision `_ - `CIFAR-10 `_ - basic, vision, fds * - `PyTorch: From Centralized To Federated `_ - `torch `_ - `CIFAR-10 `_ - basic, vision, fds * - `Flower Logistic Regression Example using scikit-learn and Flower (Quickstart Example) `_ - `scikit-learn `_ - `MNIST `_ - basic, vision, logistic regression, fds * - `Training with Sample-Level Differential Privacy using TensorFlow-Privacy Engine `_ - `tensorflow `_ - `MNIST `_ - DP, DP-SGD, basic, vision, fds, privacy * - `On-device Federated Finetuning for Speech Classification `_ - `transformers `_, `whisper `_ - `SpeechCommands `_ - finetuning, speech, transformers .. toctree:: :maxdepth: 1 :caption: Quickstart :hidden: quickstart-cpp quickstart-fastai quickstart-huggingface quickstart-jax quickstart-mlcube quickstart-mlx quickstart-monai quickstart-pandas quickstart-pytorch quickstart-pytorch-lightning quickstart-sklearn-tabular quickstart-tabnet quickstart-tensorflow xgboost-quickstart .. toctree:: :maxdepth: 1 :caption: Advanced :hidden: advanced-pytorch advanced-tensorflow flower-authentication flower-secure-aggregation vertical-fl xgboost-comprehensive .. toctree:: :maxdepth: 1 :caption: Others :hidden: android android-kotlin app-pytorch custom-metrics custom-mods embedded-devices federated-kaplan-meier-fitter fl-dp-sa fl-tabular flower-in-30-minutes flower-simulation-step-by-step-pytorch flower-via-docker-compose flowertune-llm flowertune-vit ios opacus pytorch-federated-variational-autoencoder pytorch-from-centralized-to-federated sklearn-logreg-mnist tensorflow-privacy whisper-federated-finetuning