Update app.py

app.py

@@ -1,17 +1,18 @@
+import gradio as gr
 from transformers import pipeline, AutoTokenizer
-from huggingface_hub import login
 
 # Load the tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained('prabhaskenche/toxic-comment-classification-using-RoBERTa')
 classifier = pipeline(
     'text-classification', 
     model='prabhaskenche/toxic-comment-classification-using-RoBERTa', 
-    tokenizer=tokenizer,  # Pass the tokenizer here
-    return_all_scores=True
+    tokenizer=tokenizer,
+    top_k=None  # Use top_k=None to get all scores
 )
 
 def classify(text):
     results = classifier(text)
+    # Assuming LABEL_0 is non-toxic and LABEL_1 is toxic
     non_toxic_score = next((item['score'] for item in results[0] if item['label'] == 'LABEL_0'), 0)
     toxic_score = next((item['score'] for item in results[0] if item['label'] == 'LABEL_1'), 0)
     return f"{non_toxic_score:.3f} non-toxic, {toxic_score:.3f} toxic"