base model test

app.py

@@ -1,15 +1,22 @@
 import streamlit as st
 from transformers import pipeline
 
+pipe = pipeline('sentiment-analysis')
 text = st.text_area('enter some text!')
 
-classifier = pipeline("text-classification", model="hun3359/klue-bert-base-sentiment")
-preds = classifier(text, top_k=None)
+if text:
+    out = pipe(text)
+    st.json(out)
 
-sorted_preds = sorted(preds, key=lambda x: x['score'], reverse=True)
+# text = st.text_area('enter some text!')
 
-for item in sorted_preds:
-    item['score'] = round(item['score'], 5)
+# classifier = pipeline("text-classification", model="hun3359/klue-bert-base-sentiment")
+# preds = classifier(text, top_k=None)
 
-if text:
-    st.json(sorted_preds)
+# sorted_preds = sorted(preds, key=lambda x: x['score'], reverse=True)
+
+# for item in sorted_preds:
+#     item['score'] = round(item['score'], 5)
+
+# if text:
+#     st.json(sorted_preds)