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README.md

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 This is an xlarge Chinese Whole Word Masking RoBERTa model pre-trained by [TencentPretrain](https://github.com/Tencent/TencentPretrain) introduced in [this paper](https://arxiv.org/abs/2212.06385), 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.
 
-[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 xlarge Chinese Whole Word Masking RoBERTa model. In order to facilitate users in reproducing the results, we used a publicly available corpus and word segmentation tool, and provided all training details.
+In order to facilitate users in reproducing the results, we used a publicly available corpus and word segmentation tool, and provided all training details.
 
 You can download the model either from the [UER-py Modelzoo page](https://github.com/dbiir/UER-py/wiki/Modelzoo), or via HuggingFace from the link [roberta-xlarge-wwm-chinese-cluecorpussmall](https://huggingface.co/uer/roberta-xlarge-wwm-chinese-cluecorpussmall):