Update README.md

README.md

@@ -14,7 +14,7 @@ Performance On our validation set, the model achieved:
 Accuracy: 78% F1 Score (Biased): 79% F1 Score (Non-Biased): 78%
 # How to Use
 To use this model for text classification, use the following code
-''''''
+```python
 from transformers import pipeline
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
  
@@ -23,6 +23,9 @@ model = AutoModelForSequenceClassification.from_pretrained("Social-Media-Fairnes
 classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
 result = classifier("you are stupid")
 print(result)
+'''
 # Caveats and Limitations
 The model's training data originates from a specific dataset (BABE) which might not represent all kinds of biases or content.
-The performance metrics are based on a random validation split, so the model's performance might vary in real-world applications.
+The performance metrics are based on a random validation split, so the model's performance might vary in real-world applications.
+
+Developed by Tahniat Khan