FedML
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Overview
HEALTH SCORE
Concerning*
Partial score (2/3 categories)
23out of 65
Development cadence is the lead risk. Maintainer coverage is present but not enough to offset the structural risk. Security & Supply Chain is unavailable, so weights were redistributed.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Concerning*(23/65)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 51 days.
Bus factor
No data available. Repository has not been indexed for bus factor.
Organization Diversity
Contributors span 12 organizations.
Project Achievements
Leaderboards
About
FedML is an open-source library and MLOps platform for federated learning research and production deployment. It provides a unified framework for distributed/federated training, serving, and mobile/IoT deployment with consistent APIs and modular architecture.
First commit
Software value
$7.9M
Tags
ai-agent
deep-learning
distributed-training
edge-ai
federated-learning
inference-engine
machine-learning
mlops
model-deployment
model-serving
on-device-training
License(s)
Apache-2.0
Data sources
Git
GitHub