Llm Optimization

LLM optimization refers to the techniques and processes used to enhance the performance and efficiency of large language models. This involves refining model architecture, adjusting hyperparameters, and employing strategies such as pruning or quantization to improve response accuracy and reduce computational resource requirements. The goal is to achieve better results in language understanding and generation while minimizing latency and resource consumption.