Update app.py

app.py

@@ -24,17 +24,17 @@ word_vectors = api.load("glove-wiki-gigaword-50")
 # Check for GPU and set the device accordingly
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-# Load AI Detector model and tokenizer from Hugging Face (DistilBERT)
-tokenizer_ai = AutoTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
-model_ai = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english").to(device)
+# Load AI Detector model and tokenizer from Hugging Face (roberta-base-openai-detector)
+tokenizer_ai = AutoTokenizer.from_pretrained("roberta-base-openai-detector")
+model_ai = AutoModelForSequenceClassification.from_pretrained("roberta-base-openai-detector").to(device)
 
-# AI detection function using DistilBERT
+# AI detection function using RoBERTa-based model
 def detect_ai_generated(text):
     inputs = tokenizer_ai(text, return_tensors="pt", truncation=True, max_length=512).to(device)
     with torch.no_grad():
         outputs = model_ai(**inputs)
         probabilities = torch.softmax(outputs.logits, dim=1)
-    ai_probability = probabilities[0][1].item()  # Probability of being AI-generated
+    ai_probability = probabilities[0][1].item() * 100  # Probability of being AI-generated
     return f"AI-Generated Content Probability: {ai_probability:.2f}%"
 
 # Function to get synonyms using NLTK WordNet