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Kubeflow Trainer
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Kubeflow Trainer
Kubeflow Trainer
  • Overview
  • Getting Started
  • User Guides
    • PyTorch Guide
    • PyTorch on AMD ROCm Guide
    • JAX Guide
    • JAX on TPU Guide
    • DeepSpeed Guide
    • MLX Guide
    • XGBoost Guide
    • Megatron Guide
    • Flux Guide
    • Distributed Data Cache
    • Builtin Trainer Guide
      • Overview
      • TorchTune BuiltinTrainer
    • Execute TrainJobs Locally
      • Overview
      • Local Process Backend
      • Docker Backend
      • Podman Backend
    • Configure TrainJob Lifecycle
  • Operator Guides
    • Installation
    • Migrating to Kubeflow Trainer v2
    • Runtime Guide
    • ML Policy
    • Job Template
    • Runtime Patches
    • Kubeflow Trainer Extension Framework
    • Job Scheduling
      • Overview
      • Coscheduling
      • Volcano Scheduler
      • Kueue
      • KAI Scheduler
  • Contributor Guides
    • Contributing Guide
    • Community Guide
  • Legacy Kubeflow Training Operator (v1)
    • Overview
    • Installation
    • Getting Started
    • User Guides
      • How to Fine-Tune LLMs with Kubeflow
      • How to manage Jobs in multi-cluster environment
      • PyTorch Training (PyTorchJob)
      • TensorFlow Training (TFJob)
      • PaddlePaddle Training (PaddleJob)
      • XGBoost Training (XGBoostJob)
      • JAX Training (JAXJob)
      • Job Scheduling
      • MPI Training (MPIJob)
      • Prometheus Monitoring
    • Reference
      • Architecture
      • Distributed Training with the Training Operator
      • LLM Fine-Tuning with Training Operator
    • Explanation
      • LLM Fine-Tuning with the Training Operator
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