Update README.md

README.md

@@ -10,9 +10,10 @@ tokenizer = AlbertTokenizer.from_pretrained("prajdabre/IndicBARTTokenizer", do_l
 
 # Or use tokenizer = AutoTokenizer.from_pretrained("prajdabre/IndicBARTTokenizer", do_lower_case=False, use_fast=False, keep_accents=True)
 
-model = AutoModelForSeq2SeqLM.from_pretrained("prajdabre/IndicBART")
+model = MBartForConditionalGeneration.from_pretrained("prajdabre/IndicBART")
+
+# Or use model = AutoModelForSeq2SeqLM.from_pretrained("prajdabre/IndicBART")
 
-# Or use model = MBartForConditionalGeneration.from_pretrained("prajdabre/IndicBART")
 
 # First tokenize the input and outputs. The format below is how IndicBART was trained so the input should be "Sentence </s> <2xx>" where xx is the language code. Similarly, the output should be "<2yy> Sentence </s>". 
 inp = tokenizer("I am a boy <\/s> <2en>", add_special_tokens=False, return_tensors="pt", padding=True).input_ids