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FedML

Agent

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learni...

Copy the install, test the workflow, then decide if it earns a permanent slot.

4,043
Why nowLower urgency

The signal is softer here. Treat it like a pattern source unless it solves a very specific gap.

DecisionHigh-conviction move

Copy the install, test the workflow, then decide if it earns a permanent slot.

Trial costMedium lift

Reasonable to try, but it will take more than a quick skim to get real signal.

Risk58/100

GitHub health 62/100. no security policy. 146 open issues make this testable, but not something to trust blind.

What You Are Adopting

AI Agent

Universal

Model

Multiple

Build Time

Minutes

Test This In Your Stack

One command inClean rollbackLow commitment
shieldSandboxedInstalls to ~/.claude — isolated from your projects. One command to remove.

Fastest way to find out if FedML belongs in your setup.

Copy the install command, run a real test, and back it out cleanly if it slows you down.

Try now
git clone https://github.com/FedML-AI/FedML ~/.claude/agents/fedml

Run this first. You will know quickly if the workflow earns a permanent slot.

Back out
rm -rf ~/.claude/agents/fedml

No messy cleanup loop. If it misses, remove it and keep moving.

Install Location

~/  └─ .claude/      ├─ commands/      ├─ agents/      │   └─ fedml/ ← installs here      └─ settings.json

About

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.. An open-source agent for the AI coding ecosystem.

README

FEDML Open Source: A Unified and Scalable Machine Learning Library for Running Training and Deployment Anywhere at Any Scale

Backed by TensorOpera AI: Your Generative AI Platform at Scale (https://TensorOpera.ai)

TensorOpera Documentation: https://docs.TensorOpera.ai

TensorOpera Homepage: https://TensorOpera.ai/
TensorOpera Blog: https://blog.TensorOpera.ai/

Join the Community: Slack: https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w
Discord: https://discord.gg/9xkW8ae6RV

TensorOpera® AI (https://TensorOpera.ai) is the next-gen cloud service for LLMs & Generative AI. It helps developers to launch complex model training, deployment, and federated learning anywhere on decentralized GPUs, multi-clouds, edge servers, and smartphones, easily, economically, and securely.

Highly integrated with TensorOpera open source library, TensorOpera AI provides holistic support of three interconnected AI infrastructure layers: user-friendly MLOps, a well-managed scheduler, and high-performance ML libraries for running any AI jobs across GPU Clouds.

A typical workflow is showing in figure above. When developer wants to run a pre-built job in Studio or Job Store, TensorOpera®Launch swiftly pairs AI jobs with the most economical GPU resources, auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. When running the job, TensorOpera®Launch orchestrates the compute plane in different cluster topologies and configuration so that any complex AI jobs are enabled, regardless model training, deployment, or even federated learning. TensorOpera®Open Source is unified and scalable machine learning library for running these AI jobs anywhere at any scale.

In the MLOps layer of TensorOpera AI

  • TensorOpera® Studio embraces the power of Generative AI! Access popular open-source foundational models (e.g., LLMs), fine-tune them seamlessly with your specific data, and deploy them scalably and cost-effectively using the TensorOpera Launch on GPU marketplace.
  • TensorOpera® Job Store maintains a list of pre-built jobs for training, deployment, and federated learning. Developers are encouraged to run directly with customize datasets or models on cheaper GPUs.

In the scheduler layer of TensorOpera AI

  • TensorOpera® Launch swiftly pairs AI jobs with the most economical GPU resources, auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. It supports a range of compute-intensive jobs for generative AI and LLMs, such as large-scale training, serverless deployments, and vector DB searches. TensorOpera Launch also facilitates on-prem cluster management and deployment on private or hybrid clouds.

In the Compute layer of TensorOpera AI

  • TensorOpera® Deploy is a model serving platform for high scalability and low latency.
  • TensorOpera® Train focuses on distributed training of large and foundational models.
  • TensorOpera® Federate is a federated learning platform backed by the most popular federated learning open-source library and the world’s first FLOps (federated learning Ops), offering on-device training on smartphones and cross-cloud GPU servers.
  • TensorOpera® Open Source is unified and scalable machine learning library for running these AI jobs anywhere at any scale.

Contributing

FedML embraces and thrive through open-source. We welcome all kinds of contributions from the community. Kudos to all of our amazing contributors!
FedML has adopted Contributor Covenant.

Open Live ProjectAudit Repo

Reviews0

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StaleLast commit 6mo ago
bug_report146open issues
Submitted July 21, 2020

auto_awesomeYour strongest next moves after FedML