Update app.py

app.py

@@ -15,10 +15,7 @@ def generate_preds(desc):
     #     input_desc = "GENERATE TRIGGER AND ACTION CHANNEL ONLY <pf> " + input_desc 
     # elif gen_mode=="Function":
     #     input_desc = "GENERATE BOTH CHANNEL AND FUNCTION FOR TRIGGER AND ACTION <pf> " + input_desc 
-    
-    model = EncoderDecoderModel.from_pretrained("imamnurby/rob2rand_chen_w_prefix_c_fc")
-    tokenizer = RobertaTokenizer.from_pretrained("imamnurby/rob2rand_chen_w_prefix_c_fc")
-    
+        
     input_ids = tokenizer.encode(desc, return_tensors='pt')
     
     # activate beam search and early_stopping
@@ -69,17 +66,17 @@ with demo:
     5. Click **Generate**; the generated TAPs along with the description of each component will show in the **Results**
     """)
     gr.Markdown("NOTE: **#Returned Sequences** should be LESS THAN OR EQUAL **Beam Width**")
-    # with gr.Tabs():
-    #     with gr.TabItem("Channel/Function"):    
-    #         with gr.Column():
-    # gen_mode = gr.Radio(label="Granularity", choices=["Channel", "Function"])
-    desc = gr.Textbox(label="Functionality Description", placeholder="Describe the functionality here")
-    # num_beams = gr.Slider(minimum=2, maximum=500, value=2, step=1, label="Beam Width")
-    # num_returned_seqs = gr.Slider(minimum=2, maximum=500, value=2, step=1, label="#Returned Sequences")
-    # with gr.Row():
-    generate = gr.Button("Generate")
-    # gr.Markdown("<h1><center>Results</center></h1>")
-    results = gr.Dataframe(headers=["Trigger", "Trigger Description", "Action", "Action Description"])
+    with gr.Tabs():
+        with gr.TabItem("Channel/Function"):    
+            with gr.Column():
+                # gen_mode = gr.Radio(label="Granularity", choices=["Channel", "Function"])
+                desc = gr.Textbox(label="Functionality Description", placeholder="Describe the functionality here")
+                # num_beams = gr.Slider(minimum=2, maximum=500, value=2, step=1, label="Beam Width")
+                # num_returned_seqs = gr.Slider(minimum=2, maximum=500, value=2, step=1, label="#Returned Sequences")
+                # with gr.Row():
+                generate = gr.Button("Generate")
+                # gr.Markdown("<h1><center>Results</center></h1>")
+                results = gr.Dataframe(headers=["Trigger", "Trigger Description", "Action", "Action Description"])
         
         # with gr.TabItem("Field"):    
         #     with gr.Column():