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app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Title of the app
+st.title("Hugging Face Transformers Demo")
+st.write("Enter text to analyze sentiment or generate new text:")
+
+# Load pre-trained models
+sentiment_analyzer = pipeline("sentiment-analysis")
+text_generator = pipeline("text-generation", model="gpt2")
+
+# User input
+user_input = st.text_area("Input Text")
+
+# Sentiment Analysis
+if st.button("Analyze Sentiment"):
+    if user_input:
+        result = sentiment_analyzer(user_input)
+        st.write("Sentiment Analysis Result:")
+        st.write(result)
+    else:
+        st.write("Please enter some text to analyze.")
+
+# Text Generation
+if st.button("Generate Text"):
+    if user_input:
+        result = text_generator(user_input, max_length=50)
+        st.write("Generated Text:")
+        st.write(result[0]['generated_text'])
+    else:
+        st.write("Please enter some text to generate.")

requirements.txt

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+transformers
+torch
+streamlit