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app.py
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@@ -32,6 +32,9 @@ def get_embedding(text):
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# Streamlit app setup
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st.title("Thai Full Sentence Similarity App")
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st.write("""
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### How This App Works
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This app uses a mask-filling model to predict possible words or phrases that could fill in the `<mask>` token in a given sentence. It then calculates the similarity of each prediction with the original sentence to determine the most contextually appropriate completion.
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@@ -66,7 +69,8 @@ Feel free to enter your own sentence with `<mask>` and explore the predictions!
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# User input box
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st.subheader("Input Text")
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input_text = st.text_input("Enter a sentence with `<mask>` to find similar predictions:", "
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# Ensure the input includes a `<mask>`
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if "<mask>" not in input_text:
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# Streamlit app setup
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st.title("Thai Full Sentence Similarity App")
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st.write("""
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## using Thai Law nlp dataset""")
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st.write("""
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### How This App Works
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This app uses a mask-filling model to predict possible words or phrases that could fill in the `<mask>` token in a given sentence. It then calculates the similarity of each prediction with the original sentence to determine the most contextually appropriate completion.
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# User input box
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st.subheader("Input Text")
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input_text = st.text_input("Enter a sentence with `<mask>` to find similar predictions:", "เมนูโปรดของฉันคือ <mask> ที่ทำจากวัตถุดิบสดใหม่")
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# Ensure the input includes a `<mask>`
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if "<mask>" not in input_text:
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