Flyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.

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Hey folks, I'm trying to follow this: <https://union.ai/blog-post/fine-tuning-insights-lessons-from-experimenting-with-redpajama-large-language-model-on-flyte-slack-data|https://union.ai/blog-post/fine-tuning-insights-lessons-from-experimenting-with-redpajama-large-language-model-on-flyte-slack-data>

But this link seems to be broken:
<https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/kfpytorch/pytorch_mnist.html#pytorch-elastic-training-torchrun|https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/kubernetes/kfpytorch/pytorch_mnist.html#pytorch-elastic-training-torchrun>

Is this the correct link in the docs?
<https://docs.flyte.org/projects/cookbook/en/stable/auto_examples/kfpytorch_plugin/index.html|https://docs.flyte.org/projects/cookbook/en/stable/auto_examples/kfpytorch_plugin/index.html> is there an option without kubeflow? Maybe Ray?

The plugin uses the Kubeflow training operator underneath to fine-tune the LLM.

You should also be able to use Ray as well.