Update README.md

README.md

@@ -19,13 +19,24 @@ This model can be used to generate concise summaries of input text, particularly
 ### How to Use
 You can use this model with the Hugging Face transformers library. Below is an example code snippet:
 
+```bash
+
 from transformers import PegasusForConditionalGeneration, PegasusTokenizer
 
+# Load the pre-trained model and tokenizer
 model_name = "ailm/pegsus-text-summarization"
 model = PegasusForConditionalGeneration.from_pretrained(model_name)
 tokenizer = PegasusTokenizer.from_pretrained(model_name)
 
+# Define the input text
 text = "Your input text here"
+
+# Tokenize the input text
 tokens = tokenizer(text, truncation=True, padding="longest", return_tensors="pt")
+
+# Generate the summary
 summary = model.generate(**tokens)
-print(tokenizer.decode(summary[0], skip_special_tokens=True))
+
+# Decode and print the summary
+print(tokenizer.decode(summary[0], skip_special_tokens=True))
+