Update app.py

app.py

@@ -24,8 +24,8 @@ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloa
 @torch.inference_mode()
 @spaces.GPU
 def predict_math_bot(user_message, system_message="", max_new_tokens=125, temperature=0.1, top_p=0.9, repetition_penalty=1.9, do_sample=False):
-    prompt = f"<s><INST>{user_message}{system_message}<\INST>" if system_message else user_message
-    inputs = tokenizer(prompt, return_tensors='pt', add_special_tokens=False)
+    prompt = f"<|user|>{user_message}\n<|system|>{system_message}\n<|assistant|>\n" if system_message else user_message
+    inputs = tokenizer(prompt, return_tensors='pt', add_special_tokens=True)
     input_ids = inputs["input_ids"].to(model.device)
 
     output_ids = model.generate(
@@ -44,7 +44,9 @@ def predict_math_bot(user_message, system_message="", max_new_tokens=125, temper
 def main():
     with gr.Blocks() as demo:
         gr.Markdown(title)
-        output_text = RichTextbox(label="🫡📉MetaMath", interactive=True)
+        with gr.Row():
+            user_message = gr.Code(label="🫡Enter your math query here...", language = "r" , lines=3, value="""F(x) &= \int^a_b \frac{1}{3}x^3""")
+            system_message = gr.Textbox(label="📉System Prompt", lines=2, placeholder="Optional: give precise instructions to resolve the problem provided above:")
         
         with gr.Accordion("Advanced Settings"):
             with gr.Row():
@@ -53,14 +55,13 @@ def main():
                 top_p = gr.Slider(label="Top-p (nucleus sampling)", value=0.90, minimum=0.01, maximum=0.99)
                 repetition_penalty = gr.Slider(label="Repetition penalty", value=1.9, minimum=1.0, maximum=2.0)
                 do_sample = gr.Checkbox(label="Uncheck for faster inference", value=False)
-        with gr.Row():
-            user_message = gr.Textbox(label="🫡Your Message", lines=3, placeholder="Enter your math query here...")
-            system_message = gr.Textbox(label="📉System Prompt", lines=2, placeholder="Optional: Set a scene or introduce a character...")
         gr.Button("Try🫡📉MetaMath").click(
             predict_math_bot,
             inputs=[user_message, system_message, max_new_tokens, temperature, top_p, repetition_penalty, do_sample],
             outputs=output_text
-        )     
+        )
+        output_text = RichTextbox(label="🫡📉MetaMath", interactive=True)
+             
     demo.launch()
 
 if __name__ == "__main__":