Upload 2 files

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Load the sentiment analysis pipeline
+@st.cache_resource
+def load_pipeline():
+    return pipeline("sentiment-analysis", framework="pt")
+
+sentiment_analyzer = load_pipeline()
+
+# Streamlit app title
+st.title("Sentiment Analysis App")
+st.subheader("Analyze the sentiment of your text statements")
+
+# Text input from the user
+text = st.text_area("Enter a statement for sentiment analysis", height=150)
+
+
+# Analyze sentiment when the button is clicked
+if st.button("Analyze Sentiment"):
+    if text.strip():
+        result = sentiment_analyzer(text)[0]
+        sentiment = result['label']
+        confidence = result['score']
+
+        # Display the results
+        st.write("### Results:")
+        st.write(f"**Sentiment**: {sentiment}")
+        st.write(f"**Confidence**: {confidence:.2f}")
+    else:
+        st.warning("Please enter a valid statement.")
+
+
+# Footer
+st.markdown("---")
+st.markdown("Powered by [Hugging Face](https://huggingface.co/) | Developed with ❤️ by [Shaik](https://www.linkedin.com/in/shaik-hidaythulla/)")
+

requirements.txt

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+streamlit
+pandas
+numpy
+transformers
+torch 
+torchvision
+tensorflow