Update README.md

README.md

@@ -52,7 +52,6 @@ model.eval()  # Set the model to evaluation mode
 with torch.no_grad():
     outputs = model(**encoded_input)
 
-# Get the predictions
 predictions = outputs.logits.squeeze()
 
 # Convert to numpy array if necessary
@@ -60,11 +59,10 @@ predicted_scores = predictions.numpy()
 
 trait_names = ["Agreeableness", "Openness", "Conscientiousness", "Extraversion", "Neuroticism"]
 
-# Print the predicted personality traits scores
+
 for trait, score in zip(trait_names, predicted_scores):
     print(f"{trait}: {score:.4f}")
 
-
 ##"output":
 #Agreeableness: 0.3965
 #Openness: 0.6714
@@ -75,7 +73,7 @@ for trait, score in zip(trait_names, predicted_scores):
 ```
 
 **Alternatively**, you can use the following code to make inference based on the **bash** terminal.
-```
+```python
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 import torch
 import argparse
@@ -122,12 +120,10 @@ def main():
 if __name__ == "__main__":
     main()
 ```
-```
-bash
+```bash
 python script_name.py --input "Your text here"
 ```
 or 
-```
-bash
+```bash
 python script_name.py --input path/to/your/textfile.txt
 ```