Update README.md

README.md

@@ -60,6 +60,7 @@ You can use the model and tokenizer as follows:
 
 ```python
 from transformers import AutoTokenizer, AutoModel
+import torch
 
 # Load the tokenizer
 tokenizer = AutoTokenizer.from_pretrained("hplisiecki/polemo-intensity")
@@ -67,7 +68,13 @@ tokenizer = AutoTokenizer.from_pretrained("hplisiecki/polemo-intensity")
 # Load the model
 model = AutoModel.from_pretrained("hplisiecki/polemo-intensity")
 
+# Define emotion columns
+emotion_columns = ['Happiness', 'Sadness', 'Anger', 'Disgust', 'Fear', 'Pride', 'Valence', 'Arousal']
+
 # Test the model with a sample input
 inputs = tokenizer("This is a test input.", return_tensors="pt")
 outputs = model(**inputs)
-print(outputs)
+
+# Print out the emotion ratings
+for emotion, rating in zip(emotion_columns, outputs):
+    print(f"{emotion}: {rating.item()}")