| Autor: |
Ennen, Philipp, Hsu, Po-Chun, Hsu, Chan-Jan, Liu, Chang-Le, Wu, Yen-Chen, Liao, Yin-Hsiang, Lin, Chin-Tung, Shiu, Da-Shan, Ma, Wei-Yun |
| Rok vydání: |
2023 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
In this paper we present the multilingual language model BLOOM-zh that features enhanced support for Traditional Chinese. BLOOM-zh has its origins in the open-source BLOOM models presented by BigScience in 2022. Starting from released models, we extended the pre-training of BLOOM by additional 7.4 billion tokens in Traditional Chinese and English covering a variety of domains such as news articles, books, encyclopedias, educational materials as well as spoken language. In order to show the properties of BLOOM-zh, both existing and newly created benchmark scenarios are used for evaluating the performance. BLOOM-zh outperforms its predecessor on most Traditional Chinese benchmarks while maintaining its English capability. We release all our models to the research community. |
| Databáze: |
arXiv |
| Externí odkaz: |
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