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Ever wondered how to train a large neural network across a giant cluster? Look no further!
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This is a comprehensive guide on best practices for distributed training, diagnosing errors, and fully utilizing all resources available. It is organized into sequential chapters, each with a `README.md` and a `train_llm.py` script in them. The readme will discuss both the high level concepts of distributed training, and the code changes introduced in that chapter.
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