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Update app.py
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app.py
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@@ -4,6 +4,7 @@ from stqdm import stqdm
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import pandas as pd
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from transformers import pipeline
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import json
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@@ -123,20 +124,25 @@ def main():
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elif choice=="Question Generation":
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st.subheader("Question Generation")
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st.write(" Enter the text to get questions generated !")
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text_input2 = st.text_area("Your Text","Enter the Text to complete")
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#main function to run
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if __name__ == '__main__':
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main()
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import pandas as pd
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from transformers import pipeline
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import json
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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elif choice=="Question Generation":
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st.subheader("Question Generation")
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st.write(" Enter the text to get questions generated !")
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# Load the T5 model and tokenizer
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model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
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tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
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text_input2 = st.text_area("Your Text","Enter the Text to complete")
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# Create a button to generate questions
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if st.button("Generate Questions"):
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#Encode the input text using the tokenizer
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input_ids = tokenizer.encode("generate questions: " + input_text, return_tensors="pt")
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# Use the T5 model to generate questions
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question_ids = model.generate(input_ids)
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# Decode the questions from the output ids using the tokenizer
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questions = tokenizer.decode(question_ids[0], skip_special_tokens=True)
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# Display the questions to the user
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st.write("Generated Questions:")
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st.write(questions)
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#main function to run
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if __name__ == '__main__':
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main()
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