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README.md
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@@ -54,7 +54,7 @@ We have yet to investigate the potential bias inherent in this model thoroughly.
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2. Lin, N., Fu, Y., Chen, C., Yang, Z., & Jiang, S. (2021). LaoPLM: Pre-trained Language Models for Lao. ArXiv. /abs/2110.05896
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3. MinSithu, MyanmarGPT, https://huggingface.co/jojo-ai-mst/MyanmarGPT, 1.1-SweptWood
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4. Wai Yan Nyein Naing, WYNN747/Burmese-GPT, https://huggingface.co/WYNN747/Burmese-GPT
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5. Sai Htaung Kham,saihtaungkham/BurmeseRoBERTaCLM
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6. Shliazhko, O., Fenogenova, A., Tikhonova, M., Mikhailov, V., Kozlova, A., & Shavrina, T. (2022). MGPT: Few-Shot Learners Go Multilingual. ArXiv. /abs/2204.07580
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### How to Cite this work:
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2. Lin, N., Fu, Y., Chen, C., Yang, Z., & Jiang, S. (2021). LaoPLM: Pre-trained Language Models for Lao. ArXiv. /abs/2110.05896
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| 55 |
3. MinSithu, MyanmarGPT, https://huggingface.co/jojo-ai-mst/MyanmarGPT, 1.1-SweptWood
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| 56 |
4. Wai Yan Nyein Naing, WYNN747/Burmese-GPT, https://huggingface.co/WYNN747/Burmese-GPT
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5. Sai Htaung Kham, saihtaungkham/BurmeseRoBERTaCLM
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6. Shliazhko, O., Fenogenova, A., Tikhonova, M., Mikhailov, V., Kozlova, A., & Shavrina, T. (2022). MGPT: Few-Shot Learners Go Multilingual. ArXiv. /abs/2204.07580
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### How to Cite this work:
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