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
139 stars
30 watching
77 forks
Language: Java
last commit: 17 days 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 | 52 |
federatedai/fate-board | A visualization tool for federated learning modeling to monitor and improve models | 100 |
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 | 244 |
federatedai/fate-llm | A framework for collaborative training of large language models in a privacy-preserving manner | 160 |
ibm/federated-learning-lib | A framework for collaborative distributed machine learning in enterprise environments. | 499 |
federatedai/fate | An industrial-grade framework for collaborative machine learning on private data while maintaining security and privacy | 5,723 |
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. | 1,317 |
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. | 154 |
scaleoutsystems/fedn | An open source federated learning framework designed to be secure, scalable and easy-to-use for enterprise environments | 143 |
zlz0414/feddar | A framework for federated representation learning with domain awareness in multi-model scenarios. | 2 |