Update README.md

README.md

@@ -13,10 +13,10 @@ tokenizer = BartTokenizer.from_pretrained('shahrukhx01/schema-aware-distilbart-c
 ## add NL query with table schema
 question = "What is terrence ross' nationality? </s> <col0> Player : text <col1> No. : text <col2> Nationality : text <col3> Position : text <col4> Years in Toronto : text <col5>  School/Club Team : text"
 
-inputs = tokenizer([question], max_length=1024, min_length=0, return_tensors='pt')
+inputs = tokenizer([question], max_length=1024, return_tensors='pt')
 
 # Generate SQL
-text_query_ids = model.generate(inputs['input_ids'], num_beams=4, max_length=125, early_stopping=True)
+text_query_ids = model.generate(inputs['input_ids'], num_beams=4, min_length=0, max_length=125, early_stopping=True)
 prediction = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in text_query_ids][0]
 print(prediction)
 ```