The paper explores strategies for running large sparse Mixture-of-Experts (MoE) language models on consumer hardware with limited accelerator memory, proposing a novel offloading strategy that allows for efficient execution on desktop hardware and free-tier Google Colab instances.

https://arxiv.org/abs//2312.17238

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