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Preechanon Chatthai
commited on
Update app.py
Browse files
app.py
CHANGED
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@@ -107,7 +107,20 @@ def tokenize(text):
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model = model_()
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model.load_weights("cutto_tf2.h5")
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st.title("Cutto Thai word seggmentation.")
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text = st.text_area("Enter original text!")
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if st.button("cut it!!"):
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if text:
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model = model_()
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model.load_weights("cutto_tf2.h5")
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st.title("Cutto Thai word seggmentation.")
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multi = '''# Score
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Evaluate the model performance using the test dataset divided from BEST CORPUS 2009, which comprises 10 percent, with the following scores:
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- F1-Score: 98.37
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- Precision: 98.02
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- Recall: 98.67
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# Resource Funding
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NSTDA Supercomputer center (ThaiSC) and the National e-Science Infrastructure Consortium for their support of computer facilities.
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# Citation
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If you use cutto in your project or publication, please cite the model as follows:
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ปรีชานนท์ ชาติไทย และ สัจจวัจน์ ส่งเสริม. (2567), การสรุปข้อความข่าวภาษาไทยด้วยโครงข่ายประสาทเทียม (Thai News Text Summarization Using Neural Network), วิทยาศาสตรบัณฑิต (วทบ.):ขอนแก่น, มหาวิทยาลัยขอนแก่น
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'''
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st.markdown(multi)
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text = st.text_area("Enter original text!")
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if st.button("cut it!!"):
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if text:
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