![]() All models use a vocabulary size of 51,200 and a sequence length of 2048. To demonstrate how the code scales with multiple GPUs and model sizes, we consider GPT models from 1 billion all the way to 1 trillion parameters. ![]() Our codebase is capable of efficiently training very large (hundreds of billions of parameters) language models with both model and data parallelism. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and training sophisticated natural language processing models with billions and trillions of parameters.
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