Answer / Sulekha Kumari

Improving inference speed for Large Language Models (LLMs) requires several techniques. One approach is to utilize hardware accelerators like GPUs or TPUs, which are specifically designed to handle the computational demands of deep learning models. Another strategy is model pruning, where unnecessary connections within the network are removed, reducing its complexity and speeding up inference. Quantization and knowledge distillation can also be employed to further optimize the model's performance.

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