基本信息
- 来源: blogs_podcasts
- 原始来源: https://aws.amazon.com/blogs/machine-learning/parallelize-speculative-decoding-with-p-eagle-on-amazon-sagemaker-ai
来源摘要/节选
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As large language models (LLMs) grow in size and complexity, maximizing inference throughput while minimizing latency remains a critical challenge for enterprise production deployments. Speculative decoding is one effective strategy to address this, utilizing a lightweight draft model to guess future tokens which are then verified by the target LLM in a single forward pass. While state-of-the-art frameworks like Extrapolation Algorithm for Greater Language-model Efficiency (EAGLE) have achieved impressive speedups, they encounter a hidden architectural ceiling: their draft tokens are generated autoregressively.…
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