Update app.py

app.py

@@ -15,7 +15,7 @@ pipe.to("cuda")
 
 # Load the NSFW classifier
 image_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection",device=device)
-text_classifier = pipeline("sentiment-analysis", model="michellejieli/NSFW_text_classification",device=device)
+text_classifier = pipeline("text-classification", model="eliasalbouzidi/distilbert-nsfw-text-classifier",device=device)
 classifier("I see you’ve set aside this special time to humiliate yourself in public.")
 NSFW_THRESHOLD = 0.5
 
@@ -24,7 +24,7 @@ NSFW_THRESHOLD = 0.5
 def generate_sketch(prompt, num_inference_steps, guidance_scale):
     # Classify the text for NSFW content
     text_classification = text_classifier(prompt)
-    
+    print(text_classification)
     # Check the classification results
     for result in text_classification:
         if result['label'] == 'nsfw' and result['score'] > NSFW_THRESHOLD: