Despite the success of large language models (LLMs) as general-purpose AI tools, their high demand for computational resources make their deployment challenging in many real-world scenarios. The sizes of the model and conversation state are limited by the available high-bandwidth memory, limiting the number of users that can be served and the maximum conversation length. At present��
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