Update README.md

README.md

@@ -186,7 +186,7 @@ with torch.no_grad():
 # Apply sigmoid to the logits to get probabilities
 probabilities = torch.sigmoid(outputs.logits).squeeze()
 
-# Determine a threshold for predicting labels (e.g., 0.5)
+# Determine a threshold for predicting labels
 threshold = 0.5
 predicted_label_indices = (probabilities > threshold).nonzero(as_tuple=True)[0]