Flashattention

FlashAttention is a novel attention mechanism designed to improve the efficiency of transformer-based models, particularly in the context of large language models and long-range dependencies. By optimizing the attention computation process, FlashAttention enables faster and more memory-efficient processing of sequential data, making it a relevant development in the field of natural language processing and AI research, where transformer models are increasingly being applied to complex tasks.