Fill-Mask
Transformers
PyTorch
Chinese
bert
Inference Endpoints
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@@ -27,10 +27,8 @@ model = BertModel.from_pretrained("Langboat/mengzi-bert-base")
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  |RoBERTa-wwm-ext|74.04|56.94|60.31|80.51|67.80|81.00|75.20|66.50|83.62|
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  |Mengzi-BERT-base|74.58|57.97|60.68|82.12|87.50|85.40|78.54|71.70|84.16|
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- ```bash
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  RoBERTa-wwm-ext scores are from CLUE baseline
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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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  |RoBERTa-wwm-ext|74.04|56.94|60.31|80.51|67.80|81.00|75.20|66.50|83.62|
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  |Mengzi-BERT-base|74.58|57.97|60.68|82.12|87.50|85.40|78.54|71.70|84.16|
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  RoBERTa-wwm-ext scores are from CLUE baseline
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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.