Update README.md

README.md

@@ -49,21 +49,11 @@ Implementing a pre-trained BART model for automatic text completion:
 
 Base from facebook bart /
 
-from transformers import BartForConditionalGeneration, BartTokenizer
-
-# Load pre-trained BART model
-bart_model = BartForConditionalGeneration.from_pretrained("facebook/bart-large", forced_bos_token_id=0) # takes a while to load 
-tokenizer = BartTokenizer.from_pretrained("facebook/bart-large")
-
-# Input sentence
-sent = "GeekforGeeks has a <mask> article on BART."
-
-# Tokenize the input sentence
-tokenized_sent = tokenizer(sent, return_tensors='pt')
-
-# Generate the output sequence
-generated_encoded = bart_model.generate(tokenized_sent['input_ids'])
-
-# Decode the generated sequence and print
-print(tokenizer.batch_decode(generated_encoded, skip_special_tokens=True)[0])
+    from transformers import BartForConditionalGeneration, BartTokenizer
+    bart_model = BartForConditionalGeneration.from_pretrained("facebook/bart-large", forced_bos_token_id=0) # takes a while to load 
+    tokenizer = BartTokenizer.from_pretrained("facebook/bart-large")
+    sent = "-----------your text here----- <mask> -----your text here ---"
+    tokenized_sent = tokenizer(sent, return_tensors='pt')
+    generated_encoded = bart_model.generate(tokenized_sent['input_ids'])
+    print(tokenizer.batch_decode(generated_encoded, skip_special_tokens=True)[0])