Shypd.aiThe largest open index of AI toolsLLMSpeculativeSampling is a Coding & Development tool that accelerates large language model inference using speculative decoding. It employs a smaller approximation model to generate token guesses, which are then validated by a larger target model for improved efficiency.
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LLMSpeculativeSampling is an open-source tool designed to significantly speed up inference from large language models (LLMs) through speculative decoding. This technique involves using two models: a smaller, faster approximation model to generate initial token guesses, and a larger, more accurate target model to correct and validate these guesses. By running the target model in parallel on the approximation model's outputs, LLMSpeculativeSampling achieves improved efficiency compared to decoding with the target model alone. The repository implements both Google's and Deepmind's versions of speculative sampling, offering flexibility. It supports various model pairs, including Llama2-7B and Llama2-70B, and provides features for inference and serving, making it a valuable resource for developers looking to optimize LLM performance.
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