Jan 11, 2024 · It involves two principal strategies: (1) finely segmenting the experts into mN ones and activating mK from them, allowing for a more flexible ...
In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for managing computational costs when scaling up model parameters.
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models - DeepSeek-MoE/DeepSeekMoE.pdf at main · deepseek-ai/DeepSeek-MoE.
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of ...
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Jan 11, 2024 · Preliminary efforts to scale up DeepSeekMoE to 145B parameters consistently validate its substantial advantages over the GShard architecture ...
It employs an innovative MoE architecture, which involves two principal strategies: fine-grained expert segmentation and shared experts isolation. It is trained ...
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Feb 16, 2024 · In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for managing computational costs when scaling up ...
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Jan 16, 2024 · 8.1K subscribers in the mlscaling community. ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
Jan 18, 2024 · DeepSeek-AI Proposes DeepSeekMoE: An Innovative Mixture-of-Experts (MoE) Language Model Architecture Specifically Designed Towards Ultimate ...
Jan 12, 2024 · Expert segmentation: Traditional MOE models typically have a limited number of larger experts (e.g. 16 experts). DeepSeekMoE segments each ...
