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

Backed by FEDML Nexus AI: Next-Gen Cloud Services for LLMs & Generative AI (https://nexus.fedml.ai)

FedML Documentation: https://doc.fedml.ai

FedML Homepage: https://fedml.ai/ \ FedML Blog: https://blog.fedml.ai/ \ FedML Medium: https://medium.com/@FedML \ FedML Research: https://fedml.ai/research-papers/

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FEDML® stands for Foundational Ecosystem Design for Machine Learning. FEDML Nexus 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 FEDML open source library, FEDML Nexus 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, FEDML®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, FEDML®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. FEDML®Open Source is unified and scalable machine learning library for running these AI jobs anywhere at any scale.

In the MLOps layer of FEDML Nexus AI - FEDML® 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 FEDML Launch on GPU marketplace. - FEDML® 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 FEDML Nexus AI - FEDML® 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. FEDML Launch also facilitates on-prem cluster management and deployment on private or hybrid clouds.

In the Compute layer of FEDML Nexus AI - FEDML® Deploy is a model serving platform for high scalability and low latency. - FEDML® Train focuses on distributed training of large and foundational models. - FEDML® 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. - FEDML® 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.