Update app.py

app.py

@@ -1,18 +1,29 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
+
 def main():
-  sentiment_pipeline = pipeline("sentiment-analysis",model="microsoft/resnet-50")
-  st.title("Sentiment Analysis with HuggingFace Spaces")
-  st.write("Enter a sentence to analyze its sentiment:")
-  user_input = st.text_input("")
-  if user_input:
-    result = sentiment_pipeline(user_input)
-    sentiment = result["label"]
-    confidence = result["score"]
+    # Load the model and tokenizer
+    model_name = "microsoft/resnet-50"
+    model = AutoModelForSequenceClassification.from_pretrained(model_name)
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    
+    # Initialize the pipeline
+    sentiment_pipeline = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+    
+    st.title("Sentiment Analysis with HuggingFace Spaces")
+    st.write("Enter a sentence to analyze its sentiment:")
+    
+    user_input = st.text_input("")
+    if user_input:
+        result = sentiment_pipeline(user_input)
+        sentiment = result["label"]
+        confidence = result["score"]
+
+        st.write(f"Sentiment: {sentiment}")
+        st.write(f"Confidence: {confidence:.2f}")
 
-    st.write(f"Sentiment: {sentiment}")
-    st.write(f"Confidence: {confidence:.2f}")
 if __name__ == "__main__":
-  main()
+    main()
+