DelNSP

DelNSP (Delete and Layered Next-Token Sampling) is a technique used in natural language processing to improve the quality of generated text. It works by selectively removing certain parts of a language model’s output and applying a layered sampling process, which helps produce more coherent and contextually appropriate responses. Essentially, DelNSP fine-tunes how a model predicts the next word, reducing errors and enhancing the relevance of generated content. This approach helps language models generate more accurate, fluent, and contextually suitable text for applications like chatbots, translation, and content creation.