Update README.md

README.md

@@ -17,24 +17,24 @@ Training data :
 http://dl.fbaipublicfiles.com/rephrasing/rephrasing_dataset.tar.gz
 
 ``` .py
-                                    from transformers import AutoTokenizer, AutoModelWithLMHead
-                                    tokenizer = AutoTokenizer.from_pretrained("salesken/natural_rephrase")
-                                    model = AutoModelWithLMHead.from_pretrained("salesken/natural_rephrase")
-                                    
-                                    
-                                    Input_query="Hey Siri, Send message to mom to say thank you for the delicious dinner yesterday"
-                                    query= Input_query + " ~~ "
-                                    input_ids = tokenizer.encode(query.lower(), return_tensors='pt')
-                                    sample_outputs = model.generate(input_ids,
-                                                                        do_sample=True,
-                                                                        num_beams=1, 
-                                                                        max_length=len(Input_query),
-                                                                        temperature=0.2,
-                                                                        top_k = 10,
-                                                                        num_return_sequences=1)
-                                    for i in range(len(sample_outputs)):
-                                        result = tokenizer.decode(sample_outputs[i], skip_special_tokens=True).split('||')[0].split('~~')[1]
-                                        print(result)
+from transformers import AutoTokenizer, AutoModelWithLMHead
+tokenizer = AutoTokenizer.from_pretrained("salesken/natural_rephrase")
+model = AutoModelWithLMHead.from_pretrained("salesken/natural_rephrase")
+
+
+Input_query="Hey Siri, Send message to mom to say thank you for the delicious dinner yesterday"
+query= Input_query + " ~~ "
+input_ids = tokenizer.encode(query.lower(), return_tensors='pt')
+sample_outputs = model.generate(input_ids,
+                            do_sample=True,
+                            num_beams=1, 
+                            max_length=len(Input_query),
+                            temperature=0.2,
+                            top_k = 10,
+                            num_return_sequences=1)
+for i in range(len(sample_outputs)):
+    result = tokenizer.decode(sample_outputs[i], skip_special_tokens=True).split('||')[0].split('~~')[1]
+    print(result)
 
 ```