Update README.md

README.md

@@ -44,17 +44,19 @@ This model can be loaded and used with Hugging Face's `transformers` library:
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 
-# Load the model and tokenizer
+#Load the model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained("your-username/DistilBERT-PhishGuard")
 model = AutoModelForSequenceClassification.from_pretrained("your-username/DistilBERT-PhishGuard")
 
-# Sample URL for classification
+#Sample URL for classification
 url = "http://example.com"
 inputs = tokenizer(url, return_tensors="pt", truncation=True, max_length=256)
 outputs = model(**inputs)
 predictions = torch.argmax(outputs.logits, dim=-1)
 print("Prediction:", "Phishing" if predictions.item() == 1 else "Safe")
 
+```
+
 ## Performance
 The model achieves high accuracy across different chunks of training data, with performance metrics above 98% accuracy and an AUC close to or at 1.00 in later stages. This indicates robust and reliable phishing detection across varied datasets.