Speeding up text generation with non-autoregressive language models

Large Language Models (LLMs) for generating text have recently exploded in popularity. In recent weeks, millions of users have experimented with OpenAI's ChatGPT model for tasks ranging from writing college essays to generating code. These models, however, come with a trade-off -- they are expensive and slow to run. Over the past several months, the team at Unstructured has focused on optimizing Vision Transformers (ViTs) as encoders and transformer decoders for text generation. Our goal is to convert PDFs and images to structured formats, such as JSON, fast enough for industrial use cases.