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README.md
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## Model description
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This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
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[Turc et al.](https://arxiv.org/abs/1908.08962) have shown that the standard BERT recipe is effective on a wide range of model sizes. Following their paper, we released the 24 Chinese RoBERTa models. In order to facilitate users
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You can download the 24 Chinese RoBERTa miniatures either from the [UER-py Modelzoo page](https://github.com/dbiir/UER-py/wiki/Modelzoo), or via HuggingFace from the links below:
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@@ -189,6 +189,14 @@ python3 scripts/convert_bert_from_uer_to_huggingface.py --input_model_path model
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pages={241},
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year={2019}
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}
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```
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[2_128]:https://huggingface.co/uer/chinese_roberta_L-2_H-128
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## Model description
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This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658). Besides, the models could also be pre-trained by [TencentPretrain](https://github.com/Tencent/TencentPretrain) introduced in [this paper](https://arxiv.org/pdf/2212.06385.pdf), which inherits [UER-py](https://github.com/dbiir/UER-py/) to support models with parameters above one billion, and extends it to a multimodal pre-training framework.
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[Turc et al.](https://arxiv.org/abs/1908.08962) have shown that the standard BERT recipe is effective on a wide range of model sizes. Following their paper, we released the 24 Chinese RoBERTa models. In order to facilitate users in reproducing the results, we used a publicly available corpus and provided all training details.
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You can download the 24 Chinese RoBERTa miniatures either from the [UER-py Modelzoo page](https://github.com/dbiir/UER-py/wiki/Modelzoo), or via HuggingFace from the links below:
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pages={241},
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year={2019}
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}
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@article{zhao2023tencentpretrain,
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title={TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities},
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author={Zhao, Zhe and Li, Yudong and Hou, Cheng and Zhao, Jing and others},
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journal={ACL 2023},
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pages={217},
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year={2023}
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}
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```
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[2_128]:https://huggingface.co/uer/chinese_roberta_L-2_H-128
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