Perplexity
Perplexity measures how uncertain a language model is when predicting a sequence, with lower values indicating better prediction.
Explore AIstify's latest reporting, research, and expert analysis tagged with "next-token prediction", collected in one continuously updated archive.
Perplexity measures how uncertain a language model is when predicting a sequence, with lower values indicating better prediction.
Causal language modeling trains a model to predict each next token without accessing future tokens in the sequence.
An autoregressive model predicts each next value or token using values that appeared earlier in the sequence.