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--- |
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language: |
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- zh |
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license: apache-2.0 |
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--- |
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# Mengzi-BERT base fin model (Chinese) |
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Continue trained mengzi-bert-base with 20G financial news and research reports. Masked language modeling(MLM), part-of-speech(POS) tagging and sentence order prediction(SOP) are used as training task. |
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[Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese](https://arxiv.org/abs/2110.06696) |
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## Usage |
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```python |
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from transformers import BertTokenizer, BertModel |
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tokenizer = BertTokenizer.from_pretrained("Langboat/mengzi-bert-base-fin") |
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model = BertModel.from_pretrained("Langboat/mengzi-bert-base-fin") |
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``` |
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## Citation |
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If you find the technical report or resource is useful, please cite the following technical report in your paper. |
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``` |
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@misc{zhang2021mengzi, |
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title={Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese}, |
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author={Zhuosheng Zhang and Hanqing Zhang and Keming Chen and Yuhang Guo and Jingyun Hua and Yulong Wang and Ming Zhou}, |
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year={2021}, |
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eprint={2110.06696}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
