THE GREATEST GUIDE TO LARGE LANGUAGE MODELS

It includes coaching the model with large precision after which quantizing the weights and activations to decrease precision over the inference period. This allows for a lesser product measurement whilst keeping high functionality. As quantization represents model parameters with decreased-little bit integer (e.g., int8), the design dimension and r