Update README.md

README.md

@@ -23,12 +23,16 @@ To generate text using the model:
 
     
     tokenizer = MBart50TokenizerFast.from_pretrained("MRNH/mbart-english-grammar-corrector", src_lang="en_XX", tgt_lang="en_XX")
-    input = tokenizer("I was here yesterday to studying",text_target="I was here yesterday to study", return_tensors='pt')
-    output = model.generate(input["input_ids"],attention_mask=input["attention_mask"],forced_bos_token_id=tokenizer_it.lang_code_to_id["en_XX"])
+    
+    input = tokenizer("I was here yesterday to studying",
+                      text_target="I was here yesterday to study", return_tensors='pt')
+                      
+    output = model.generate(input["input_ids"],attention_mask=input["attention_mask"],
+                            forced_bos_token_id=tokenizer_it.lang_code_to_id["en_XX"])
 
 
-Training of the model is performed using the following loss computatation:
+Training of the model is performed using the following loss computation based on the hidden state output h:
 
-    hidden_state.logits, hidden_state.loss = model(input_ids=input["input_ids"],
+    h.logits, h.loss = model(input_ids=input["input_ids"],
                                                   attention_mask=input["attention_mask"],
                                                   labels=input["labels"])