BART

BART, or Bidirectional and Auto-Regressive Transformers, is a type of machine learning model developed for natural language processing. It combines the benefits of understanding context from both directions in a sentence (like reading both ways) and generating text based on what has been previously written. This makes it effective for tasks like summarizing text, answering questions, and filling in gaps in sentences. By predicting words in a sentence based on surrounding words, BART can produce coherent and contextually relevant language, making it useful for applications such as chatbots, translation, and content creation.