removed cache

app.py

@@ -10,8 +10,13 @@ def predict_cyberbullying_probability(sentence, tokenizer, model):
     # Preprocess the input sentence
     inputs = tokenizer(sentence, padding='max_length', return_token_type_ids=False, return_attention_mask=True, truncation=True, max_length=512, return_tensors='pt')
 
-
+    print("==========")
+    print(inputs)
+    print("==========")
+    
     attention_mask = inputs['attention_mask'].flatten()
+    print("==========")
+    print(attention_mask)
     inputs = inputs['input_ids'].flatten()
     # print("\n\ninputs\n\n", inputs)
     # Disable gradient computation
@@ -19,7 +24,8 @@ def predict_cyberbullying_probability(sentence, tokenizer, model):
         # Forward pass
         outputs = model(inputs, attention_mask=attention_mask)
 
-        probs = torch.sigmoid(outputs.logits.flatten())
+        probs = torch.sigmoid(outputs.logits.unsqueeze(1).flatten())
+
         
     
     res = probs.numpy().tolist()
@@ -73,8 +79,6 @@ st.image(image, use_column_width=True)
 
 labels = ['comment', 'toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
 
-# toxic_list = st.cache(comments.comments)
-
 
 with st.form("my_form"):
     #select model
@@ -85,9 +89,10 @@ with st.form("my_form"):
         tweet = st.text_area(label="Enter Text:",value=default)
         submitted = st.form_submit_button("Analyze textbox")
         random = st.form_submit_button("Analyze a random 😈😈😈 tweet")
-
+        
         if random:
             tweet = comments.comments[randint(0, 354)]
+            st.write(tweet)
         
 
         df = perform_cyberbullying_analysis(tweet)