mGPT: Few-Shot Learners Go Multilingual

Author:

Shliazhko Oleh1,Fenogenova Alena2,Tikhonova Maria34,Kozlova Anastasia5,Mikhailov Vladislav6,Shavrina Tatiana78910

Affiliation:

1. Independent Researcher, The Netherlands. olehshliazhko@gmail.com

2. SaluteDevices, Russia. alenush93@gmail.com

3. Independent Researcher, The Netherlands

4. SaluteDevices, Russia. mtihonova@hse.ru

5. SaluteDevices, Russia. anastasi2510@gmail.com

6. SaluteDevices, Russia. vvmkhlvv@gmail.com

7. SaluteDevices, Russia

8. AIRI, Russia

9. AI Center, NUST MISiS, Russia

10. Institute of Linguistics RAS, Russia. rybolos@gmail.com

Abstract

Abstract This paper introduces mGPT, a multilingual variant of GPT-3, pretrained on 61 languages from 25 linguistically diverse language families using Wikipedia and the C4 Corpus. We detail the design and pretraining procedure. The models undergo an intrinsic and extrinsic evaluation: language modeling in all languages, downstream evaluation on cross-lingual NLU datasets and benchmarks in 33 languages, and world knowledge probing in 23 languages. The in-context learning abilities are on par with the contemporaneous language models while covering a larger number of languages, including underrepresented and low-resource languages of the Commonwealth of Independent States and the indigenous peoples in Russia. The source code and the language models are publicly available under the MIT license.

Publisher

MIT Press

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An information-theoretic analysis of targeted regressions during reading;Cognition;2024-08

2. A Cross Search Method for Data Augmentation in Neural Machine Translation;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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