Create app.py

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+def sentiment_analysis(text, model_name):
+    model = AutoModelForSequenceClassification.from_pretrained(model_name)
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+    classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
+    result = classifier(text)
+
+    return result[0]['label']
+
+def main():
+    st.title("Sentiment Analysis App")
+    text = st.text_input("Enter text:")
+    model_name = st.selectbox("Select a pretrained model", ["bert-base-uncased", "distilbert-base-uncased", "roberta-base"])
+
+    if st.button("Analyze"):
+        with st.spinner('Analyzing...'):
+            sentiment = sentiment_analysis(text, model_name)
+            st.write("Sentiment:", sentiment)
+
+if __name__ == '__main__':
+    main()
+