Update app.py

app.py

@@ -1,3 +1,4 @@
+import streamlit as st
 import gradio as gr
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
@@ -626,9 +627,15 @@ def main():
 
 
 if __name__ == "__main__":
+    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.write(output)