Update app.py

app.py

@@ -609,32 +609,17 @@ def compute_model_card_evaluation_results(tokenizer, model_checkpoint, raw_datas
     result = trainer.evaluate()
     return result
 
-"""
-
-def main():
-    try:
-        interface = GradioInterface()
-        demo = interface.create_interface()
-        demo.launch(
-            server_name="0.0.0.0",
-            show_error=True,
-            share=True
-        )
-    except Exception as e:
-        logger.error(f"Error starting application: {e}")
-        raise
-"""
-
-
 if __name__ == "__main__":
 
     st.title("Hugging Face Model Evaluation Demo")
 
     # Create an input text box
-    input_text = st.text_input("Enter model and dataset identifiers", "")
-    
+    input_text = st.text_area("Enter model and dataset identifiers", "")
+
+    # hardcode input data
     model_checkpoint = "sgugger/glue-mrpc"
-    dataset_name = "nyu-mll/glue" 
+    dataset_name = "nyu-mll/glue"
+    
     metric = load("glue", "mrpc")
     tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
     in_container = False
@@ -644,4 +629,4 @@ if __name__ == "__main__":
     tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
     output = compute_model_card_evaluation_results(tokenizer, model_checkpoint, raw_datasets, metric)
     print(json.dumps(output))
-    st.write(output)
+    st.text_area(label="Output Data:", value=output, height=350)