Efficient Inference

Telescopic Language Models: One Training Run for Endless Compute Budgets

伸縮自如的語言模型：單次訓練即可適應多種運算資源預算的 Telescopic LM

This research introduces Telescopic Language Models (TLM), which use stochastic prefix supervision to enable a single Transformer to act as a valid language model at any layer depth, serving diverse compute budgets from a single training run.