FATE-Serving
Federated learning server
A high-performance serving system for federated learning models, providing support for online algorithms, real-time inference, and model management.
A scalable, high-performance serving system for federated learning models
138 stars
30 watching
77 forks
Language: Java
last commit: about 1 month ago federated-learninginferencemodel-servingmodel-versioningmonitor
Related projects:
| Repository | Description | Stars |
|---|---|---|
| federatedai/fate-client | Provides tools and APIs for designing, scheduling, and running federated machine learning jobs in a secure and efficient manner. | 3 |
| federatedai/fate-flow | An end-to-end federated learning workflow platform for managing data and models across multiple parties | 53 |
| federatedai/fate-board | A visualization tool for federated learning modeling to monitor and improve models | 101 |
| federatedai/fate-test | A collection of tools and tests for evaluating the performance of federated machine learning systems | 1 |
| federatedai/fate-community | Documentation repository for a community-driven project focused on federated AI technology development and governance. | 25 |
| federatedai/eggroll | A framework for distributed machine learning | 242 |
| federatedai/fate-llm | A framework for collaborative training of large language models in a privacy-preserving manner | 166 |
 ibm/federated-learning-lib | A framework for collaborative distributed machine learning in enterprise environments. | 500 |
| federatedai/fate | Enables secure collaboration on data among multiple parties while protecting privacy and security | 5,750 |
| federatedai/fate-cloud | An infrastructure tool for managing and securing collaborative data networks across organizations | 30 |
 alibaba/federatedscope | A comprehensive platform for federated learning, providing an event-driven architecture and flexible customization for various tasks in academia and industry. | 1,335 |
 felisat/clustered-federated-learning | An implementation of a federated learning method to optimize multiple models simultaneously while maintaining user privacy. | 160 |
 omarfoq/fedem | Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. | 157 |
 scaleoutsystems/fedn | An open source federated learning framework designed to be secure, scalable and easy-to-use for enterprise environments | 145 |
 zlz0414/feddar | A framework for federated representation learning with domain awareness in multi-model scenarios. | 2 |