Update README.md

README.md

@@ -61,3 +61,17 @@ To sum up,my model performs nearly as well as the SOTA rule-based model evaluate
 
 (It's worth mentioning that even though I tried my best to conduct objective tests, the testsets I could find were more or less different from what they introduced in the paper.)
 
+## How to use
+
+
+```python
+from transformers import BartTokenizer, BartForConditionalGeneration
+tokenizer = BartTokenizer.from_pretrained("MarkS/QA2D")
+model = BartForConditionalGeneration.from_pretrained("MarkS/QA2D")
+
+input_text = "question: what day is it today? answer: Tuesday"
+input = tokenizer(input_text, return_tensors='pt')
+output = model.generate(input.input_ids)
+result = tokenizer.batch_decode(output, skip_special_tokens=True)
+```
+