REDUCE LLM principle training time A research team is developing a new large-scale generative model and is encountering significant challenges with training time and memory consumption on their existing hardware. Which of the following strategies would best address these scalability and computational requirements? pruning and quantization to reduce model size mixed-precision training for memory efficiency 节流to reduce model size Pruning（剪枝）- reduce components 是指从神经网络中移除不重要的权重或神经元，以减少模型的复杂度。 权重剪枝（Weight Pruning）：移除权重值接近于零的连接。 结构剪枝（Structured Pruning）：移除整个神经元、通道或卷积核，更适合硬件加速。 Quantization（量化）- reduce density in each component ...