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bayartsogt/bert-base-mongolian-uncased bayartsogt/bert-base-mongolian-uncased
31 downloads
last 30 days

pytorch

tf

Contributed by

bayartsogt Bayartsogt Yadamsuren
3 models

How to use this model directly from the 🤗/transformers library:

			
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from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bayartsogt/bert-base-mongolian-uncased") model = AutoModelForMaskedLM.from_pretrained("bayartsogt/bert-base-mongolian-uncased")

BERT-BASE-MONGOLIAN-UNCASED

Link to Official Mongolian-BERT repo

Model description

This repository contains pre-trained Mongolian BERT models trained by tugstugi, enod and sharavsambuu. Special thanks to nabar who provided 5x TPUs.

This repository is based on the following open source projects: google-research/bert, huggingface/pytorch-pretrained-BERT and yoheikikuta/bert-japanese.

How to use

from transformers import pipeline, AlbertTokenizer, BertForMaskedLM

tokenizer = AlbertTokenizer.from_pretrained('bayartsogt/bert-base-mongolian-uncased')
model = BertForMaskedLM.from_pretrained('bayartsogt/bert-base-mongolian-uncased')

## declare task ##
pipe = pipeline(task="fill-mask", model=model, tokenizer=tokenizer)

## example ##
input_  = 'Миний [MASK] хоол идэх нь тун чухал.'

output_ = pipe(input_)
for i in range(len(output_)):
    print(output_[i])

Training data

Mongolian Wikipedia and the 700 million word Mongolian news data set [Pretraining Procedure]

BibTeX entry and citation info

@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/}}
}