New Technical Report from @EkagraRanjan: Contrary to what you might expect, MoE-based LLMs make spec...
- MoE 模型与推测解码结合可显著提升效率。
- 传统观点认为 MoE 增加专家数量会降低收益，但实际效果相反。
- 报告提供对生产环境中 MoE 模型优化的具体见解。
Cohere on X: "New Technical Report from @EkagraRanjan: Contrary to what you might expect, MoE-based LLMs make speculative decoding even more effective. Read more on our blog:" / X
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New Technical Report from
: Contrary to what you might expect, MoE-based LLMs make speculative decoding even more effective. Read more on our blog:
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Ekagra Ranjan
@EkagraRanjan
·
10h
Ever wondered how Speculative Decoding interacts with production MoE models? Conventional wisdom: MoE + speculative decoding = too many experts to load, gains disappear. Reality: MoE amplifies speculative decoding. Checkout Cohere Blogpost: https://cohere.com/blog/mixture-o f-experts-models-get-more-from-speculative-decoding…
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-  Cohere @cohere Follow Click to Follow cohere Empowering enterprises with private, powerful AI. Join us: http://cohere.com/careers
-  Ekagra Ranjan @EkagraRanjan Follow Click to Follow EkagraRanjan LLM Inference & Efficiency @cohere • Ex-@Microsoft • Open Source @PyTorch • Intern @IiscNLP (MALL Lab, IISc), @IITKgp • B. Tech @IITGuwahati • Machine Learning
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