Create app.py

app.py

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+# Step 2: Import necessary libraries
+import streamlit as st
+from transformers import pipeline
+
+# Step 3: Load pre-trained model and tokenizer
+qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad", tokenizer="distilbert-base-cased")
+
+# Step 4: Define Streamlit app
+def main():
+    # Set app title
+    st.title("Question Answering with ALBERT")
+
+    # Input context
+    context = st.text_area("Enter the context:")
+
+    # Input questions
+    num_questions = st.number_input("Enter the number of questions:", min_value=1, max_value=10, step=1)
+    questions = [st.text_input(f"Enter question {i + 1}:") for i in range(num_questions)]
+
+    # Ask questions and display answers
+    if st.button("Get Answers"):
+        for i, question in enumerate(questions):
+            if question:
+                answer = qa_pipeline({"context": context, "question": question})
+                st.write(f"Answer {i + 1}: {answer['answer']}")
+
+# Step 5: Run Streamlit app
+if __name__ == "__main__":
+    main()