Bole: Efficient Tree Speculation for Hybrid-Attention Language Models
内核-运行时协同设计:通过闭式树验证、值域分块GPU核和因子化推测状态,将混合注意力LLM的树投机解码吞吐量提升至自回归解码的4.72×
2 posts tagged with "linear-attention"
内核-运行时协同设计:通过闭式树验证、值域分块GPU核和因子化推测状态,将混合注意力LLM的树投机解码吞吐量提升至自回归解码的4.72×
A speculative decoding runtime for stateful linear-attention models that verifies chains and trees with topology-aware kernels, stores compact factors to recover accepted states, and uses confidence pruning plus a target-aligned EAGLE-style drafter.