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Download app_stream.py from manan/Score-Clinical-Patient-Notes: direct link, hf CLI and curl.
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- Download file 372 Bytes
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https://huggingface.co/spaces/manan/Score-Clinical-Patient-Notes/resolve/main/app_stream.py
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hf download hf://spaces/manan/Score-Clinical-Patient-Notes/app_stream.py
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curl -L -o app_stream.py https://huggingface.co/spaces/manan/Score-Clinical-Patient-Notes/resolve/main/app_stream.py
372 Bytes
| import streamlit as st | |
| import model | |
| st.title('Identify Key Phrases in Patient Notes from Medical Licensing Exams') | |
| pn_history = st.text_area("Patient History") | |
| feature_text = st.text_input('Feature Text') | |
| label='submit' | |
| if st.button(label): | |
| if pn_history and feature_text != '': | |
| pred = model.get_predictions(pn_history, feature_text) | |
| st.write(pred) |