OPTIMIZING LARGE LANGUAGE MODEL TRAINING USING FP4 QUANTIZATION

Summary from the TLDR AI newsletter

One of the key levers that can be pulled to reduce training and inference costs is quantization. Getting these models to run at lower precision saves on the number of GPUs and FLOPs needed for training. This work shows, on a small scale of 100B tokens, how to train at FP4.