Text Generation Inference

Text Generation Inference is the process in machine learning where a model, typically a neural network, generates coherent and contextually relevant text based on a given input. This is a common task in natural language processing (NLP).

How Text Generation Inference Works

A model trained on a large corpus of text learns the probabilities of word sequences. Given an initial input or prompt, the model uses these probabilities to generate subsequent words, aiming to form grammatically correct and contextually appropriate sentences. For example, language models like GPT-3 use text generation inference to create complete articles, stories, or conversational responses based on initial prompts.