Update README.md

README.md

@@ -1,3 +1,51 @@
 ---
+language: 
+  - zh
 license: apache-2.0
+
+tags:
+- bert
+- NLU
+- Sentiment
+
+inference: true
+
+widget:
+- text: "今天心情不好"
+
 ---
+# Erlangshen-MegatronBert-1.3B-Semtiment, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
+We collect 8  sentiment datasets in the Chinese domain for finetune, with a total of 227347 samples. Our model is mainly based on [MegatronBert-1.3B](https://huggingface.co/IDEA-CCNL/Erlangshen-MegatronBert-1.3B)
+
+## Usage
+```python
+from transformers import BertForSequenceClassification
+from transformers import BertTokenizer
+import torch
+
+tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Sentiment')
+model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Sentiment')
+
+text='今天心情不好'
+
+output=model(torch.tensor([tokenizer.encode(text)]))
+print(torch.nn.functional.softmax(output.logits,dim=-1))
+
+```
+## Scores on downstream chinese tasks
+|    Model   | ASAP-SENT    |  ASAP-ASPECT  | ChnSentiCorp    |
+| :--------:    | :-----:  | :----:  | :-----:   | 
+| Erlangshen-Roberta-110M-Sentiment | 97.77     |   97.31    | 96.61     |
+| Erlangshen-Roberta-330M-Sentiment | 97.9      |   97.51    | 96.66      |  
+| Erlangshen-MegatronBert-1.3B-Sentiment | 98.1     |   97.8    | 97      |
+
+## Citation
+If you find the resource is useful, please cite the following website in your paper.
+```
+@misc{Fengshenbang-LM,
+  title={Fengshenbang-LM},
+  author={IDEA-CCNL},
+  year={2021},
+  howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
+}
+```