Training a Llama 3B model with a 3M token context on a single 8xH100 node fails because model parameters alone exhaust GPU memory. @m_ryabinin explains how Unti
Training large language models with extensive context windows, such as 3 million tokens, faces memory limitations on hardware like 8xH100 nodes. Researchers have developed a method called Untied Ulysses to overcome these constraints, enabling the training of models at 8B and 32B scales with significantly longer sequences than previously possible. AI
IMPACT Enables training of larger models with significantly longer context windows, pushing the boundaries of LLM capabilities.