VOOZH about

URL: https://huggingface.co/papers/2304.01196

⇱ Paper page - Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data


Papers
arxiv:2304.01196

Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data

Published on Apr 3, 2023
Authors:
,
,

Abstract

A pipeline uses ChatGPT to generate a multi-turn chat corpus, which is then used to parameter-efficiently tune LLaMA, resulting in the Baize model with guardrails.

Chat models, such as ChatGPT, have shown impressive capabilities and have been rapidly adopted across numerous domains. However, these models are only accessible through a restricted API, creating barriers for new research and progress in the field. We propose a pipeline that can automatically generate a high-quality multi-turn chat corpus by leveraging ChatGPT to engage in a conversation with itself. Subsequently, we employ parameter-efficient tuning to enhance LLaMA, an open-source large language model. The resulting model, named Baize, demonstrates good performance in multi-turn dialogues with guardrails that minimize potential risks. The Baize models and data are released for research purposes only at https://github.com/project-baize/baize. An online demo is also available at https://huggingface.co/spaces/project-baize/baize-lora-7B.

Community

· Sign up or log in to comment

Get this paper in your agent:

hf papers read 2304.01196

Models citing this paper 21

Browse 21 models citing this paper

Datasets citing this paper 5

Browse 5 datasets citing this paper

Spaces citing this paper 151

Browse 151 spaces citing this paper

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.