Update README.md

README.md

@@ -5,11 +5,11 @@ license: apache-2.0
 widget:
 - text: "生活的真谛是[MASK]。"
 ---
-# Zhouwenwang-1.3B model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
-Zhouwenwang-1.3B apply a new unified structure, and jointly developed by the IDEA-CCNL and Zhuiyi Technology. In the pre-training, the model considers LM (Language Model) and MLM (Mask Language Model) tasks uniformly, and adds rotational position coding, so that the model has the ability to generate and understand. Zhouwenwang-1.3B is the largest model for LM and MLM tasks in the Chinese field. It will continue to be optimized in the direction of model scale, knowledge integration, and supervision task assistance.
+# Zhouwenwang-Unified-1.3B model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
+Zhouwenwang-Unified-1.3B apply a new unified structure, and jointly developed by the IDEA-CCNL and Zhuiyi Technology. In the pre-training, the model considers LM (Language Model) and MLM (Mask Language Model) tasks uniformly, and adds rotational position coding, so that the model has the ability to generate and understand. Zhouwenwang-Unified-1.3B is the largest model for LM and MLM tasks in the Chinese field. It will continue to be optimized in the direction of model scale, knowledge integration, and supervision task assistance.
 
 ## Usage
-There is no structure of Zhouwenwang-1.3B in [Transformers](https://github.com/huggingface/transformers), you can run follow code to get structure of Zhouwenwang-1.3B from [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)
+There is no structure of Zhouwenwang-Unified-1.3B in [Transformers](https://github.com/huggingface/transformers), you can run follow code to get structure of Zhouwenwang-Unified-1.3B from [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)
 
  ```shell
  git clone https://github.com/IDEA-CCNL/Fengshenbang-LM.git
@@ -21,9 +21,9 @@ from fengshen import RoFormerModel
 from fengshen import RoFormerConfig
 from transformers import BertTokenizer
 
-tokenizer = BertTokenizer.from_pretrained("IDEA-CCNL/Zhouwenwang-1.3B")
-config = RoFormerConfig.from_pretrained("IDEA-CCNL/Zhouwenwang-1.3B")
-model = RoFormerModel.from_pretrained("IDEA-CCNL/Zhouwenwang-1.3B")
+tokenizer = BertTokenizer.from_pretrained("IDEA-CCNL/Zhouwenwang-Unified-1.3B")
+config = RoFormerConfig.from_pretrained("IDEA-CCNL/Zhouwenwang-Unified-1.3B")
+model = RoFormerModel.from_pretrained("IDEA-CCNL/Zhouwenwang-Unified-1.3B")
 
 
 ```
@@ -39,8 +39,8 @@ import numpy as np
 sentence = '清华大学位于'
 max_length = 32
 
-tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Zhouwenwang-1.3B")
-model = RoFormerModel.from_pretrained("IDEA-CCNL/Zhouwenwang-1.3B")
+tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Zhouwenwang-Unified-1.3B")
+model = RoFormerModel.from_pretrained("IDEA-CCNL/Zhouwenwang-Unified-1.3B")
 
 for i in range(max_length):
     encode = torch.tensor(
@@ -61,7 +61,7 @@ print(sentence)
 |     Model| afqmc    |  tnews  | iflytek    |  ocnli  |  cmnli  | wsc  | csl  |
 | :--------:    | :-----:  | :----:  | :-----:   | :----: | :----: | :----: | :----: |
 | roberta-wwm-ext-large | 0.7514      |   0.5872    | 0.6152      |   0.777    | 0.814    | 0.8914    | 0.86    |
-| Zhouwenwang-1.3B | 0.7463     |   0.6036    | 0.6288     |   0.7654   | 0.7741    | 0.8849    | 0. 8777   |
+| Zhouwenwang-Unified-1.3B | 0.7463     |   0.6036    | 0.6288     |   0.7654   | 0.7741    | 0.8849    | 0. 8777   |
 
 ## Citation
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