Efficient Guided Generation for Large Language Models

07/19/2023
by   Brandon T. Willard, et al.
0

In this article we describe an efficient approach to guiding language model text generation with regular expressions and context-free grammars. Our approach adds little to no overhead to the token sequence generation process, and makes guided generation feasible in practice. An implementation is provided in the open source Python library Outlines.

READ FULL TEXT

page 9

page 11

research
10/07/2022

Visualize Before You Write: Imagination-Guided Open-Ended Text Generation

Recent advances in text-to-image synthesis make it possible to visualize...
research
01/31/2023

Grounding Language Models to Images for Multimodal Generation

We propose an efficient method to ground pretrained text-only language m...
research
01/06/2021

TextBox: A Unified, Modularized, and Extensible Framework for Text Generation

We release an open library, called TextBox, which provides a unified, mo...
research
12/26/2022

TextBox 2.0: A Text Generation Library with Pre-trained Language Models

To facilitate research on text generation, this paper presents a compreh...
research
01/24/2022

Relational Memory Augmented Language Models

We present a memory-augmented approach to condition an autoregressive la...
research
02/12/2021

On Efficient Training, Controllability and Compositional Generalization of Insertion-based Language Generators

Auto-regressive language models with the left-to-right generation order ...
research
06/19/2023

Guiding Language Models of Code with Global Context using Monitors

Language models of code (LMs) work well when the surrounding code in the...

Please sign up or login with your details

Forgot password? Click here to reset