Efficient Attention Mechanisms for LLMs

10 repos

Libraries and implementations of optimized attention algorithms for large language models, with a focus on reducing computational cost and memory usage during inference and training. The cluster centers on CUDA-accelerated approaches like Flash Attention, which achieve efficiency gains through algorithmic improvements and hardware-aware optimizations. Most repositories are Python-based implementations and research codebases exploring variants of fast attention, making this a practical resource for practitioners building or fine-tuning LLM inference systems.

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