FedML

by FedML-AIVerified

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.

4,062
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765
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Python
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8/23/2026
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⚠️ Third-Party Software Notice

This skill is third-party open-source software developed and hosted independently on GitHub. SkillTip is an informational directory and does not control or maintain the underlying repository. Any security checks displayed are automated and limited in scope. Review the source code before installing.

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Installation

Add to your Claude Code skills directory:

# Add to your Claude Code skills
git clone https://github.com/FedML-AI/FedML

Getting Started

Guides for using skills like FedML.

Security Report

Verified

Last scanned: —

{
  "status": "PASSED",
  "issues": []
}

README.md

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.

Frequently Asked Questions

What is FedML?

FedML is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by FedML-AI. 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. It has 4,062 GitHub stars.

Is FedML safe to use?

Yes. FedML passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install FedML?

Clone the repository with "git clone https://github.com/FedML-AI/FedML" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is FedML written in?

FedML is primarily written in Python. It is open-source under FedML-AI on GitHub, so you can review or fork the full source.

Are there alternatives to FedML?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh FedML against similar tools.

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