Create README.md

README.md

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+---
+language: 
+  - zh
+license: apache-2.0
+---
+
+
+# Mengzi-BERT base model (Chinese)
+
+Pretrained model on 300G Chinese corpus. Masked language modeling(MLM), part-of-speech(POS) tagging and sentence order prediction(SOP) are used as training task.
+
+[Mengzi: A lightweight yet Powerful Chinese Pre-trained Language Model](www.example.com)
+
+## Usage
+
+```python
+from transformers import BertTokenizer, BertModel
+tokenizer = BertTokenizer.from_pretrained("Langboat/mengzi-bert-base")
+model = BertModel.from_pretrained("Langboat/mengzi-bert-base")
+```
+
+## Scores on nine chinese tasks (without any data augmentation)
+|Model|AFQMC|TNEWS|IFLYTEK|CMNLI|WSC|CSL|CMRC|C3|CHID|
+|-|-|-|-|-|-|-|-|-|-|
+|CLUE RoBERTa-wwm-ext Baseline|74.04|56.94|60.31|80.51|67.80|81|75.20|66.5|83.62|
+|Mengzi-BERT-base|74.58|57.97|60.68|82.12|87.50|85.4|78.54|71.7|0|
+
+## Citation
+If you find the technical report or resource is useful, please cite the following technical report in your paper.
+```
+example
+```