Update app.py

app.py

@@ -51,7 +51,8 @@ def process_with_model(pec_number):
     inputs = tokenizer(pec_number, return_tensors="pt")
     with torch.no_grad():
         outputs = model(**inputs)
-    return outputs.last_hidden_state.mean(dim=1).squeeze().tolist()
+    # Instead of returning the full model output, return just a simple confirmation
+    return "Model processed successfully."
 
 # Combine both functions to create a prediction
 def predict(pec_number):
@@ -61,7 +62,7 @@ def predict(pec_number):
 
         name = get_name(pec_number, df)
         model_output = process_with_model(pec_number)
-        return f"Name: {name}\nModel Output: {model_output}"
+        return f"Name: {name}"  # Only display the name
     except Exception as e:
         print(f"An error occurred: {e}")
         return f"Error: {e}"
@@ -72,7 +73,7 @@ iface = gr.Interface(
     inputs=gr.Textbox(lines=1, placeholder="Enter PEC Number..."),
     outputs="text",
     title="PEC Number to Name Lookup",
-    description="Enter a PEC number to retrieve the corresponding name and process it with a Hugging Face model."
+    description="Enter a PEC number to retrieve the corresponding name."
 )
 
 # Run the Gradio interface