Index

nlp/app/routes.py

@@ -42,7 +42,7 @@ def index():
             # For CNN, assuming preprocessing is handled differently or is built-in
             text = basic_process(input_field)
             text = cnn_process(text)
-            predictions_proba = cnn.predict([text])
+            predictions_proba = cnn.predict(text)
             pred = (predictions_proba > 0.5).astype(int)[0]  # Assuming binary classification
             proba = predictions_proba[0]
         elif model_choice == 'bert':
@@ -51,7 +51,6 @@ def index():
             text = tokenizer(input_field, return_tensors="pt")
             with torch.no_grad():
                 outputs = model(**text)
-
             predicted_class = torch.argmax(outputs.logits).item()
 
         return render_template('myform.html', title='', form=form,