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Zero-shot learning is a machine learning paradigm where models recognize objects or concepts without having seen any labeled examples during training. It leverages semantic information or auxiliary data to generalize knowledge to new, unseen classes.
Instructor is an embedding model designed to generate vector representations of text that capture semantic meaning, enabling improved performance in various natural language processing tasks. It is used primarily to convert textual data into numerical format for machine learning applications.