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Kubeflow Trainer
Kubeflow Trainer
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    • Execute TrainJobs Locally
      • Overview
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    • Configure TrainJob Lifecycle
  • Operator Guides
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    • Runtime Guide
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    • Kubeflow Trainer Extension Framework
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  • Contributor Guides
    • Contributing Guide
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  • 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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ExplanationΒΆ

Explanation for Training Operator Features

Old Version

This page is about Kubeflow Training Operator V1, for the latest information check the Kubeflow Trainer V2 documentation.

Follow this guide for migrating to Kubeflow Trainer V2.

  • LLM Fine-Tuning with the Training Operator
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LLM Fine-Tuning with Training Operator
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