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