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--- |
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language: "mn" |
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tags: |
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- mongolian |
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- cased |
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--- |
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# BERT-BASE-MONGOLIAN-CASED |
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[Link to Official Mongolian-BERT repo](https://github.com/tugstugi/mongolian-bert) |
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## Model description |
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This repository contains pre-trained Mongolian [BERT](https://arxiv.org/abs/1810.04805) models trained by [tugstugi](https://github.com/tugstugi), [enod](https://github.com/enod) and [sharavsambuu](https://github.com/sharavsambuu). |
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Special thanks to [nabar](https://github.com/nabar) who provided 5x TPUs. |
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This repository is based on the following open source projects: [google-research/bert](https://github.com/google-research/bert/), |
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[huggingface/pytorch-pretrained-BERT](https://github.com/huggingface/pytorch-pretrained-BERT) and [yoheikikuta/bert-japanese](https://github.com/yoheikikuta/bert-japanese). |
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#### How to use |
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```python |
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from transformers import pipeline, AutoTokenizer, BertForMaskedLM |
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tokenizer = AutoTokenizer.from_pretrained('tugstugi/bert-base-mongolian-cased') |
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model = BertForMaskedLM.from_pretrained('tugstugi/bert-base-mongolian-cased') |
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## declare task ## |
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pipe = pipeline(task="fill-mask", model=model, tokenizer=tokenizer) |
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## example ## |
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input_ = 'Миний [MASK] хоол идэх нь тун чухал.' |
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output_ = pipe(input_) |
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for i in range(len(output_)): |
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print(output_[i]) |
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## Output ## |
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# {'sequence': '[CLS] Миний хувьд хоол идэх нь тун чухал.[SEP]', 'score': 0.8734784722328186, 'token': 95, 'token_str': '▁хувьд'} |
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# {'sequence': '[CLS] Миний бодлоор хоол идэх нь тун чухал.[SEP]', 'score': 0.09788835793733597, 'token': 6320, 'token_str': '▁бодлоор'} |
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# {'sequence': '[CLS] Миний хүү хоол идэх нь тун чухал.[SEP]', 'score': 0.0027510314248502254, 'token': 590, 'token_str': '▁хүү'} |
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# {'sequence': '[CLS] Миний бие хоол идэх нь тун чухал.[SEP]', 'score': 0.0014857524074614048, 'token': 267, 'token_str': '▁бие'} |
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# {'sequence': '[CLS] Миний охин хоол идэх нь тун чухал.[SEP]', 'score': 0.0013575413031503558, 'token': 1116, 'token_str': '▁охин'} |
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``` |
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## Training data |
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Mongolian Wikipedia and the 700 million word Mongolian news data set [[Pretraining Procedure](https://github.com/tugstugi/mongolian-bert#pre-training)] |
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### BibTeX entry and citation info |
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```bibtex |
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@misc{mongolian-bert, |
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author = {Tuguldur, Erdene-Ochir and Gunchinish, Sharavsambuu and Bataa, Enkhbold}, |
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title = {BERT Pretrained Models on Mongolian Datasets}, |
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year = {2019}, |
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publisher = {GitHub}, |
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journal = {GitHub repository}, |
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howpublished = {\url{https://github.com/tugstugi/mongolian-bert/}} |
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} |
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``` |
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