Update app.py

app.py

@@ -49,9 +49,9 @@ except RuntimeError as e:
 
 # Instantiate and prepare model for training.
 dfModel, dfState, _ = init_df(model_base_dir="DeepFilterNet3")
-dfModel.to(device)#torch.device("cuda"))
+dfModel.to(torch.device("cuda"))
 pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
-pipeline.to(device)#torch.device("cuda"))
+pipeline.to(torch.device("cuda"))
 
 # Store results for viewing and further processing
 if 'results' not in st.session_state:
@@ -129,11 +129,12 @@ if uploaded_file_paths is not None:
         st.session_state.results.append([])
     while (len(st.session_state.summaries) < len(valid_files)):
         st.session_state.summaries.append([])
-    st.info(f'{len(valid_files)} valid files: {[fi.name for fi in valid_files]}')
+
+st.info(f'{len(valid_files)} valid files: {[fi.name for fi in valid_files]}')
     
 if st.button("Analyze All Audio",key=f"button_all"):
     if len(valid_files) == 0:
-        tab.error('Upload file(s) first!')
+        st.error('Upload file(s) first!')
     else:
         start_time = time.time()
         totalFiles = len(valid_files)