Ray 2.8.0

  • Welcome to Ray!

Ray

  • Overview
  • Getting Started
  • Installation
  • Use Cases
  • Example Gallery
  • Ecosystem
  • Ray Core
  • Ray Data
  • Ray Train
  • Ray Tune
  • Ray Serve
  • Ray RLlib
  • More Libraries
  • Ray Clusters
    • Key Concepts
    • Deploying on Kubernetes
      • Getting Started with KubeRay
      • User Guides
      • Examples
        • Ray Train XGBoostTrainer on Kubernetes
        • Train PyTorch ResNet model with GPUs on Kubernetes
        • Serve a StableDiffusion text-to-image model on Kubernetes
        • Serve a MobileNet image classifier on Kubernetes
        • Serve a text summarizer on Kubernetes
        • RayJob Batch Inference Example
      • KubeRay Ecosystem
      • KubeRay Benchmarks
      • KubeRay Troubleshooting
      • API Reference
    • Deploying on VMs
    • Collecting and monitoring metrics
    • Configuring and Managing Ray Dashboard
    • Applications Guide
    • FAQ
    • Ray Cluster Management API
    • Usage Stats Collection
  • Monitoring and Debugging
  • Developer Guides
  • Glossary
  • Security
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Examples

Examples#

This section presents example Ray workloads to try out on your Kubernetes cluster.

  • Ray Train XGBoostTrainer on Kubernetes (CPU-only)

  • Train PyTorch ResNet model with GPUs on Kubernetes

  • Serve a MobileNet image classifier on Kubernetes (CPU-only)

  • Serve a StableDiffusion text-to-image model on Kubernetes

  • Serve a text summarizer on Kubernetes

  • RayJob Batch Inference Example

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(Advanced) Deploying a static Ray cluster without KubeRay

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Ray Train XGBoostTrainer on Kubernetes

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By The Ray Team
© Copyright 2023, The Ray Team.