test

app.py

@@ -9,14 +9,26 @@ model = AutoModelForCausalLM.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 with gr.Blocks() as demo:
-    with gr.Row():
-        vicuna_chatbot = gr.Chatbot(label="vicuna-7b", live=False)
-        llama_chatbot = gr.Chatbot(label="llama-7b", live=False)
-        gpt_chatbot = gr.Chatbot(label="gpt-3.5", live=False)
-    with gr.Row():
-        prompt = gr.Textbox(show_label=False, placeholder="Enter prompt")
-        send_button_Chunk = gr.Button("Send", scale=0)
-    clear = gr.ClearButton([prompt, vicuna_chatbot])
+    gr.Markdown("<center># LLM Evaluator With Linguistic Scrutiny</center>")
+
+    with gr.Tab("POS"):
+        with gr.Row():
+            vicuna_chatbot = gr.Chatbot(label="vicuna-7b", live=False)
+            llama_chatbot = gr.Chatbot(label="llama-7b", live=False)
+            gpt_chatbot = gr.Chatbot(label="gpt-3.5", live=False)
+        with gr.Row():
+            prompt = gr.Textbox(show_label=False, placeholder="Enter prompt")
+            send_button_Chunk = gr.Button("Send", scale=0)
+        clear = gr.ClearButton([prompt, vicuna_chatbot])
+    with gr.Tab("Chunk"):
+        with gr.Row():
+            vicuna_chatbot = gr.Chatbot(label="vicuna-7b", live=False)
+            llama_chatbot = gr.Chatbot(label="llama-7b", live=False)
+            gpt_chatbot = gr.Chatbot(label="gpt-3.5", live=False)
+        with gr.Row():
+            prompt = gr.Textbox(show_label=False, placeholder="Enter prompt")
+            send_button_Chunk = gr.Button("Send", scale=0)
+        clear = gr.ClearButton([prompt, vicuna_chatbot])
 
     def respond(message, chat_history, chatbot_idx):
         input_ids = tokenizer.encode(message, return_tensors="pt")