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--- |
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license: mit |
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language: |
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- my |
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pipeline_tag: text-generation |
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metrics: |
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- code_eval |
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library_name: transformers |
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tags: |
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- burmese |
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- gpt2 |
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- pre-trained |
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--- |
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The Simbolo's Myanmarsar-GPT symbol is trained on a dataset of 1 million Burmese data and pre-trained using the GPT-2 architecture. Its purpose is to serve as a foundational pre-trained model for the Burmese language, facilitating fine-tuning for specific applications of different tasks such as creative writing, chatbot, machine translation etc. |
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### How to use |
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```python |
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!pip install transformers |
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from transformers import pipeline |
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pipe = pipeline('text-generation',model='Simbolo-Servicio/myanmar-burmese-gpt', tokenizer='Simbolo-Servicio/myanmar-burmese-gpt',config={'max_length':500}) |
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pipe('မြန်မာဘာသာစကား') |
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# |
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``` |
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### Data |
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The data utilized comprises 1 million sentences sourced from Wikipedia. |
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### Contributors |
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Main Contributor: Sa Phyo Thu Htet (https://github.com/SaPhyoThuHtet) |
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Wikipedia Data Crawling: Kaung Kaung Ko Ko, Phuu Pwint Thinzar Kyaing |
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Releasing the Model: Eithandaraung, Ye Yint Htut, Thet Chit Su, Naing Phyo Aung |
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### Limitations and bias |
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We have yet to thoroughly investigate the potential bias inherent in this model. Regarding transparency, it's important to note that the model is primarily trained on data from the Unicode Burmese(Myanmar) language. |
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### References |
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1. Jiang, Shengyi & Huang, Xiuwen & Cai, Xiaonan & Lin, Nankai. (2021). Pre-trained Models and Evaluation Data for the Myanmar Language. 10.1007/978-3-030-92310-5_52. |
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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. Dr. Wai Yan Nyein Naing, WYNN747/Burmese-GPT, https://huggingface.co/WYNN747/Burmese-GPT |
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5. Sai Htaung Kham,saihtaungkham/BurmeseRoBERTaCLM |
