Llm Pre Training, Llm Architecture, Model Quantization, Scaling Model Training, Llm Domain Adaptation.
numbers. For instance, if a model with one billion parameters requires approximately 80 gigabytes of GPU RAM at full 32-bit precision, quantization can yield significant memory savings. By employing 16-bit half precision (FP16), the memory requirement can be reduced by 50%, resulting in only 40