Update README.md

README.md

@@ -9,7 +9,9 @@ Trained Strategy :
  - In-batch Negatives : 12 Epoch, by KLUE MRC dataset, random sampling between Sparse Retrieval(TF-IDF) top 100 passage per each query
  
 I'm not confident about this model will work in other dataset or corpus. 
-'''
+
+<pre>
+<code>
 from Transformers import AutoTokenizer, BertPreTrainedModel, BertModel
 
 class BertEncoder(BertPreTrainedModel):
@@ -31,4 +33,5 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 q_encoder = BertEncoder.from_pretrained("thingsu/koDPR_question")
 p_encoder = BertEncoder.from_pretrained("thingsu/koDPR_context")
 
-'''
+</code>
+</pre>