Question and Answering

We are excited to announce the release of version 1.0 of our question-answering model, a compact 128 million parameter model designed for efficient performance.

The main application of this model is to generate question and answer pairs or to answer a user question given the context. This can also be used to enhance and expand the capabilities of Retrieval-Augmented Generation (RAG) systems.

Additionally, this model can help reduce the costs associated with building and maintaining question-answering systems by utilizing routing Large Language Models (LLMs), making it a valuable resource for developers and researchers in the field.