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