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GeezerVison is showing github.com — TensorOpera (Formerly FEDML)

README.md

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.

fedml-nexus-ai-overview.png

TensorOpera AI: Your Generative AI Platform at Scale
https://TensorOpera.ai

TensorOpera Open Source: The unified and scalable ML library for large-scale distributed training, model serving, and federated learning
https://github.com/FedML-AI/FedML

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

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.

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  1. FedML FedML Public

    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 o…

    Python 4.1k 771

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  • FedML Public

    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.

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    FedML-AI/FedML's past year of commit activity
    Python 4,069 Apache-2.0 771 122 (46 issues need help) 28 Updated Nov 11, 2026
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    HTML 1 0 0 0 Updated Apr 19, 2025
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    Shell 1 5 5 3 Updated Jan 3, 2025
  • openai_trtllm Public Forked from npuichigo/openai_trtllm

    OpenAI compatible API for TensorRT LLM triton backend

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    Rust 0 MIT 33 0 0 Updated Jul 24, 2024
  • FedCV Public

    FedCV: An Industrial-grade Federated Learning Framework for Diverse Computer Vision Tasks

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    FedML-AI/FedCV's past year of commit activity
    66 23 6 2 Updated Jun 25, 2024
  • lorax Public Forked from predibase/lorax

    Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs

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    Python 1 Apache-2.0 370 0 0 Updated Jun 15, 2024
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    Python 0 0 0 0 Updated Jun 7, 2024
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    Python 2 Apache-2.0 0 0 0 Updated Dec 29, 2023
  • FedGraphNN Public

    FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

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    FedML-AI/FedGraphNN's past year of commit activity
    184 42 7 1 Updated Dec 19, 2023
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