Phoenix: Democratizing ChatGPT across Languages
Zhihong Chen, Feng Jiang, Junying Chen, Tiannan Wang, Fei Yu, Guiming, Chen, Hongbo Zhang, Juhao Liang, Chen Zhang, Zhiyi Zhang, Jianquan Li, Xiang, Wan, Benyou Wang, Haizhou Li
TL;DR
This paper introduces Phoenix, a large language model designed to democratize access to ChatGPT across multiple languages, including low-resource and non-Latin languages, promoting wider accessibility and usage.
Contribution
The paper presents Phoenix, a new open-source multilingual language model that achieves competitive performance in English, Chinese, and low-resource languages, expanding accessibility.
Findings
Achieves competitive performance in English and Chinese
Excels in low-resource Latin and non-Latin languages
Available data, code, and models for public use
Abstract
This paper presents our efforts to democratize ChatGPT across language. We release a large language model "Phoenix", achieving competitive performance among open-source English and Chinese models while excelling in languages with limited resources (covering both Latin and non-Latin languages). We believe this work will be beneficial to make ChatGPT more accessible, especially in countries where people cannot use ChatGPT due to restrictions from OpenAI or local goverments. Our data, code, and models are available at https://github.com/FreedomIntelligence/LLMZoo.
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Topic Modeling