Update README.md

README.md

@@ -14,11 +14,14 @@ DialogSum dataset (115056 Records) was used to fine-tune the model for Punctuati
 <pre>
 
 from transformers import T5Tokenizer, TFT5ForConditionalGeneration
+
 tokenizer = T5Tokenizer.from_pretrained('SJ-Ray/Re-Punctuate')
 model = TFT5ForConditionalGeneration.from_pretrained('SJ-Ray/Re-Punctuate')
+
 input_text = 'the story of this brave brilliant athlete whose very being was questioned so publicly is one that still captures the imagination'
 inputs = tokenizer.encode("punctuate: " + input_text, return_tensors="tf") 
 result = model.generate(inputs)
+
 decoded_output = tokenizer.decode(result[0], skip_special_tokens=True)
 print(decoded_output)
 
@@ -26,3 +29,8 @@ print(decoded_output)
 <h4> Example: </h4>
 <b>Input:</b>  the story of this brave brilliant athlete whose very being was questioned so publicly is one that still captures the imagination <br>
 <b>Output:</b> The story of this brave, brilliant athlete, whose very being was questioned so publicly, is one that still captures the imagination.
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
+
+<h4> Connect on: </h4>
+<a href='www.linkedin.com/in/suraj-kumar-710382a7'> <i class="fa fa-linkedin-square" style="font-size:36px;color:#0e76a8"></i></a>