test again

app.py

@@ -1,21 +1,25 @@
 import streamlit as st
-import torch as torch
+import torch
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoConfig
 from transformers import pipeline
-from PIL import Image
 
-model_name = "peace4ever/roberta-large-finetuned-mongolian_v3"  
-pipeline = pipeline(task="sentiment-analysis", model=model_name)
+model_name = "peace4ever/roberta-large-finetuned-mongolian_v3"
+pipeline = pipeline(task="sentiment-analysis", model=model_name)  # Load pre-trained pipeline
 
 st.title("Эерэг? Сөрөг эсвэл аль нь ч биш?")
 text = st.text_area("Өгүүлбэр оруулна уу?")
 
 if text is not None:
-    
-    col1, col2 = st.columns(2)
     predictions = pipeline(text)
-    col2.header("Probabilities")
-    print(predictions)
+
+    col1, col2 = st.columns(2)
+    col1.header("Sentiment")
+    col2.header("Probability")
+
+    for label, probability in zip(predictions[0]["label"], predictions[0]["score"]):
+        col1.write(label)  # Display sentiment label (e.g., "POSITIVE", "NEGATIVE")
+        col2.write(f"{probability:.2f}")  # Display probability with 2 decimal places
+
 
 
 # tokenizer = AutoTokenizer.from_pretrained(model_name)