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  # Azza - Grounded Q/A Conversational Agent 🤖
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  > We applied BERT to the Stanford Question Answering Dataset (SQuAD) to achieve *natural and grounded* human-level performance on question answering.
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  <p align="center">
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  <img width="734" alt="Screenshot 2023-03-27 at 10 45 57" src="https://user-images.githubusercontent.com/65676392/227976366-b4560691-28ed-4556-9068-e2d6d4bd8bb9.png">
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  </p>
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  # Pipeline
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  1. Key-phrase extraction from the user's question [1].
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  # References
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- [1] https://huggingface.co/ml6team/keyphrase-extraction-kbir-inspec
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- [2] https://arxiv.org/pdf/1810.04805v2.pdf
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- [3] https://rajpurkar.github.io/SQuAD-explorer/
 
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  # Azza - Grounded Q/A Conversational Agent 🤖
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  > We applied BERT to the Stanford Question Answering Dataset (SQuAD) to achieve *natural and grounded* human-level performance on question answering.
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+ <br>
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  <p align="center">
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  <img width="734" alt="Screenshot 2023-03-27 at 10 45 57" src="https://user-images.githubusercontent.com/65676392/227976366-b4560691-28ed-4556-9068-e2d6d4bd8bb9.png">
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  </p>
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+ <br>
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  # Pipeline
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  1. Key-phrase extraction from the user's question [1].
 
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  # References
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+ [1] https://huggingface.co/ml6team/keyphrase-extraction-kbir-inspec <br>
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+ [2] https://arxiv.org/pdf/1810.04805v2.pdf <br>
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+ [3] https://rajpurkar.github.io/SQuAD-explorer/ <br>