Llm, AI, Deep Learning, Optimization.
Post-Training Quantization (PTQ) It involves the quantization of a trained model after the completion of its training phase. By reducing the precision of model parameters, typically from 32-bit floating-point representation to 8-bit integers, PTQ offers alluring benefits such as reduced memory