Update app.py

app.py

@@ -280,20 +280,28 @@ if __name__ == "__main__":
 
     st.title("Hugging Face Model Evaluation Demo")
 
-    # Create an input text box
-    input_text = st.text_area("Enter model and dataset identifiers", "")
+    with st.form("my_form"):
 
-    # hardcode input data
-    model_checkpoint = "sgugger/glue-mrpc"
-    dataset_name = "nyu-mll/glue"
+        # Create an input text box
+        input_text1 = st.text_area("Enter model and dataset identifiers", "")
+        input_text2 = st.text_area("Enter model and dataset identifiers", "")
+
+        # Every form must have a submit button.
+        submitted = st.form_submit_button("Submit")
+
+        if submitted:
+            print(input_text1, input_text2) 
+            # hardcode input data
+            model_checkpoint = "sgugger/glue-mrpc"
+            dataset_name = "nyu-mll/glue"
     
-    metric = load("glue", "mrpc")
-    tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
-    in_container = False
-    model_checkpoint = model_checkpoint
-    raw_datasets = load_dataset(dataset_name, "mrpc")
-    metric = load("glue", "mrpc")
-    tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
-    output = compute_model_card_evaluation_results(tokenizer, model_checkpoint, raw_datasets, metric)
-    print(json.dumps(output))
-    st.text_area(label="Output Data:", value=output, height=350)
+            metric = load("glue", "mrpc")
+            tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+            in_container = False
+            model_checkpoint = model_checkpoint
+            raw_datasets = load_dataset(dataset_name, "mrpc")
+            metric = load("glue", "mrpc")
+            tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+            output = compute_model_card_evaluation_results(tokenizer, model_checkpoint, raw_datasets, metric)
+            print(json.dumps(output))
+            st.text_area(label="Output Data:", value=output, height=350)