{"id":13790251,"url":"https://github.com/beiyuouo/fedhf","last_synced_at":"2025-04-19T18:07:45.092Z","repository":{"id":40365785,"uuid":"415992499","full_name":"beiyuouo/fedhf","owner":"beiyuouo","description":"🔨 A Flexible Federated Learning Simulator for Heterogeneous and 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support Asynchronous Federated Learning)"],"sub_categories":["2018"],"readme":"# FedHF\n\n\u003cimg src=\"https://raw.githubusercontent.com/beiyuouo/fedhf/main/docs/assets/logo.svg\" alt=\"logo\" style=\"width:100%;\"\u003e\n\n[FedHF](https://github.com/beiyuouo/fedhf) is a loosely coupled, **H**eterogeneous resource supported, and **F**lexible federated learning framework. \n\n*Accelerate your research*\n\n![](https://img.shields.io/github/stars/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/github/forks/beiyuouo/fedhf?style=flat-square) ![https://www.bj-yan.top/fedhf/](https://img.shields.io/badge/document-building-blue?style=flat-square) ![](https://img.shields.io/github/languages/code-size/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/github/issues/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/github/issues-pr/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/pypi/pyversions/fedhf?style=flat-square) ![](https://img.shields.io/pypi/l/fedhf?style=flat-square) [![Downloads](https://pepy.tech/badge/fedhf)](https://pepy.tech/project/fedhf)\n\n[![Discord](https://img.shields.io/discord/942746457855889469.svg?logo=discord\u0026logoColor=white\u0026logoWidth=20\u0026labelColor=7289DA\u0026label=Discord\u0026style=flat-square)](https://discord.gg/AsvX9Q75)\n\n\n## Features\n\n- [x] Losely coupled\n- [x] Heterogeneous resource supported\n- [x] Flexible federated learning framework\n- [x] Support for asynchronous aggregation\n- [x] Support for multiple federated learning algorithms\n\n## Algorithms Supported\n\n### Synchronous Aggregation\n\n- [x] **[FedAvg]** Communication-Efficient Learning of Deep Networks from Decentralized Data(*AISTAT*) [[paper]](https://arxiv.org/abs/1602.05629.pdf)\n\n### Asynchronous Aggregation\n\n- [x] **[FedAsync]** Asynchronous Federated Optimization(*OPT2020*) [[paper]](https://arxiv.org/abs/1903.03934)\n\n### Tiered Aggregation\n\n- [ ] **[TiFL]** TiFL: A Tier-based Federated Learning System (*HPDC 2020*) [[paper]](https://dl.acm.org/doi/abs/10.1145/3369583.3392686)\n\n## Getting Start\n\n```sh\npip install fedhf\n\n# If you want to use wandb to view log, please login first\nwandb login\n```\n\nYou can see the [Document](https://www.bj-yan.top/fedhf/) for more details.\n\n## Contributing\n\nFor more information, please see the [Contributing](https://www.bj-yan.top/fedhf/contributing/) page.\n\n## Citation\n\n\u003e *In progress*\n\n## Licence\n\nThis work is provided under [Apache License Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).\n\n## Acknowledgement\n\nMany thanks to [FedLab](https://github.com/SMILELab-FL/FedLab) and [FedML](https://github.com/FedML-AI/FedML) for their great work.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbeiyuouo%2Ffedhf","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbeiyuouo%2Ffedhf","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbeiyuouo%2Ffedhf/lists"}