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Overview

  • Welcome to NVIDIA FLARE
  • NVIDIA FLARE Roadmap
  • What’s New in FLARE v2.8.0
  • Industry Use Cases

Get Started

  • Installation
  • Quick Start Series
  • Migration Guide

User Guide

  • Client API Usage
  • NVFlare Job Recipe
  • Available Recipes
  • FLARE API
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  • Running Flower in NVIDIA FLARE
  • Experiment Tracking
  • Federated XGBoost
  • Data Preparation & Heterogeneity
  • CLI Tools

Examples & Tutorials

  • Example Applications
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  • Self-Paced-Training Tutorials
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Large Models & LLM

  • Federated LLM Fine-Tuning
  • Message Quantization
  • Memory Management
  • FLARE Tensor Downloader
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  • Decomposer for Large Objects

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  • Running FLARE in Docker
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  • NVIDIA FLARE Security Overview
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Developer Guide

  • Architecture & Developer Guide

Reference

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NVIDIA FLARE
  • nvflare
  • nvflare package
  • nvflare.app_opt package
  • nvflare.app_opt.xgboost package
  • nvflare.app_opt.xgboost.histogram_based_v2 package
  • nvflare.app_opt.xgboost.histogram_based_v2.proto package
  • View page source

nvflare.app_opt.xgboost.histogram_based_v2.proto package

Submodules

  • nvflare.app_opt.xgboost.histogram_based_v2.proto.federated_pb2 module
  • nvflare.app_opt.xgboost.histogram_based_v2.proto.federated_pb2_grpc module
    • Federated
      • Federated.Allgather()
      • Federated.AllgatherV()
      • Federated.Allreduce()
      • Federated.Broadcast()
    • FederatedServicer
      • FederatedServicer.Allgather()
      • FederatedServicer.AllgatherV()
      • FederatedServicer.Allreduce()
      • FederatedServicer.Broadcast()
    • FederatedStub
    • add_FederatedServicer_to_server()

Module contents

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