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Consistency LLM: converting LLMs to parallel decoders accelerates inference 3.5x

by Siqi Kou*, Lanxiang Hu*, Zhezhi He, Zhijie Deng, Hao Zhang hao-ai-lab.github.io published 2024-05-069 min read

TL;DR: LLMs have been traditionally regarded as sequential decoders, decoding one token after another. In this blog, we show pretrained LLMs can be easily taught to operate as efficient parallel decoders. We introduce Consistency Large Language Models (CLLMs), a new family of parallel decoders capable of reducing…
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May 8, 2024Consistency LLM: converting LLMs to parallel decoders accelerates inference 3.5x by zhisbug46198

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