Update README.md

README.md

@@ -47,21 +47,23 @@ An autoencoder is a special type of neural network that learns to encode an inpu
 
 Implementing a pre-trained BART model for automatic text completion: 
 
-'''
-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") 
+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."
-  
 
-tokenized_sent = tokenizer(sent, return_tensors='pt') 
-  
+# Tokenize the input sentence
+tokenized_sent = tokenizer(sent, return_tensors='pt')
+
+# Generate the output sequence
+generated_encoded = bart_model.generate(tokenized_sent['input_ids'])
 
-generated_encoded = bart_model.generate(tokenized_sent['input_ids']) 
-  
-print(tokenizer.batch_decode(generated_encoded, skip_special_tokens=True)[0]) 
+# Decode the generated sequence and print
+print(tokenizer.batch_decode(generated_encoded, skip_special_tokens=True)[0])
 
-'''