Megatron-LM training guide for GPT-2 on NVIDIA GPUs — setup, preprocessing, and distributed training

AI Impact Summary

Megatron-LM provides a GPU-optimized path for pretraining transformer models, but the workflow is non-trivial to set up. The guide covers end-to-end steps: via NVIDIA's PyTorch container or a CUDA stack, preparing data with CodeParrot and the datasets library, and launching distributed training with tensor and model parallelism, plus fused optimizers and kernel fusion. For business teams, this enables faster GPT-2 sized pretraining on multi-GPU nodes, but success hinges on proper infrastructure (NGC container, vocab/merges in place, and distributed launch configuration).