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Abstract:Autoregressive decoding is bottlenecked by its sequential nature. Speculative decoding has become a standard way to accelerate inference by using a fast draft model to predict upcoming tokens from a slower target model, and then verifying them in parallel with a single target model forward pass. However, speculative decoding itself relies on a sequential dependence between speculation and verification. We introduce speculative speculative decoding (SSD) to parallelize these operations. While a verification is ongoing, the draft model predicts likely verification outcomes and prepares speculations pre-emptively for them. If the actual verification outcome is then in the predicted set, a speculation can be returned immediately, eliminating drafting overhead entirely. We identify three key challenges presented by speculative speculative decoding, and suggest principled methods to solve each. The result is Saguaro, an optimized SSD algorithm. Our implementation is up to 2x faster than optimized speculative decoding baselines and up to 5x faster than autoregressive decoding with open source inference engines.
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В удаленном от Украины почти в 2 тысячи километров регионе России ввели дистант из-за БПЛА08:47
Like a groan-inducing jokeThe answer is Corny.
Nashvillians, meanwhile, had tired of the city’s style of law enforcement. Al Gore, a liberal resident, had just become Vice-President, and the Criminal Justice Center was now seen as an embarrassing relic. In 1994, Nashville elected a new sheriff: Gayle Ray, a former English professor with no background in law enforcement. She saw inmates as citizens first, she told me, adding, “It matters to the community what condition they come out in.”