Meta LLaMA 开源模型动态

Sequel to: Learning to Skip Blocks: Self-Discovered Ultrametric Routing for Hardware-Accelerated Sparse Attention Abstract We present Llama Surgery , a method for injecting learned block-sparse attention topologies into pre-trained dense language models without retraining from scratch, distillation, or post-hoc pruning. Starting from a frozen Llama 3.1 8B, we surgically replace each attention laye…

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