Update README.md

README.md

@@ -12,4 +12,47 @@ datasets:
 - segyges/OpenWebText2
 language:
 - en
----
+library_name: transformers
+---
+from transformers import pipeline
+
+class ContentFilter:
+    def __init__(self):
+        # Load pre-trained model for text classification
+        self.classifier = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-offensive")
+    
+    def filter_content(self, text, threshold=0.75):
+        # Classify the input text
+        result = self.classifier(text)[0]
+        
+        # Determine if the content is offensive based on the classification
+        is_offensive = result['label'] == 'LABEL_1' and result['score'] > threshold
+        
+        return {
+            "text": text,
+            "is_offensive": is_offensive,
+            "confidence": result['score']
+        }
+
+# Create an instance of the ContentFilter
+content_filter = ContentFilter()
+
+# Function to test the filter
+def test_filter():
+    texts = [
+        "Have a nice day!",
+        "You are an idiot!",
+        "The weather is lovely.",
+        "I hate you so much."
+    ]
+    
+    for text in texts:
+        result = content_filter.filter_content(text)
+        print(f"Text: {result['text']}")
+        print(f"Is offensive: {result['is_offensive']}")
+        print(f"Confidence: {result['confidence']:.4f}")
+        print()
+
+# Run the test
+if __name__ == "__main__":
+    test_filter()