--- language: "mn" tags: - bert - mongolian - cased --- # BERT-LARGE-MONGOLIAN-CASED [Link to Official Mongolian-BERT repo](https://github.com/tugstugi/mongolian-bert) ## Model description 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). Special thanks to [nabar](https://github.com/nabar) who provided 5x TPUs. This repository is based on the following open source projects: [google-research/bert](https://github.com/google-research/bert/), [huggingface/pytorch-pretrained-BERT](https://github.com/huggingface/pytorch-pretrained-BERT) and [yoheikikuta/bert-japanese](https://github.com/yoheikikuta/bert-japanese). #### How to use ```python from transformers import pipeline, AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained('tugstugi/bert-large-mongolian-cased', use_fast=False) model = AutoModelForMaskedLM.from_pretrained('tugstugi/bert-large-mongolian-cased') ## declare task ## pipe = pipeline(task="fill-mask", model=model, tokenizer=tokenizer) ## example ## input_ = 'Монгол улсын [MASK] Улаанбаатар хотоос ярьж байна.' output_ = pipe(input_) for i in range(len(output_)): print(output_[i]) ## output ## # {'sequence': 'Монгол улсын нийслэл Улаанбаатар хотоос ярьж байна.', 'score': 0.9779232740402222, 'token': 1176, 'token_str': 'нийслэл'} # {'sequence': 'Монгол улсын Нийслэл Улаанбаатар хотоос ярьж байна.', 'score': 0.015034765936434269, 'token': 4059, 'token_str': 'Нийслэл'} # {'sequence': 'Монгол улсын Ерөнхийлөгч Улаанбаатар хотоос ярьж байна.', 'score': 0.0021413620561361313, 'token': 325, 'token_str': 'Ерөнхийлөгч'} # {'sequence': 'Монгол улсын ерөнхийлөгч Улаанбаатар хотоос ярьж байна.', 'score': 0.0008035294013097882, 'token': 1215, 'token_str': 'ерөнхийлөгч'} # {'sequence': 'Монгол улсын нийслэлийн Улаанбаатар хотоос ярьж байна.', 'score': 0.0006434018723666668, 'token': 356, 'token_str': 'нийслэлийн'} ``` ## Training data Mongolian Wikipedia and the 700 million word Mongolian news data set [[Pretraining Procedure](https://github.com/tugstugi/mongolian-bert#pre-training)] ### BibTeX entry and citation info ```bibtex @misc{mongolian-bert, author = {Tuguldur, Erdene-Ochir and Gunchinish, Sharavsambuu and Bataa, Enkhbold}, title = {BERT Pretrained Models on Mongolian Datasets}, year = {2019}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/tugstugi/mongolian-bert/}} } ```