updated description for all tabs
Browse files
app.py
CHANGED
@@ -135,7 +135,7 @@ if selected == "App":
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st.markdown(
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'Here you can extract the nearest neighbours to a chosen lemma. \
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Please select one or more time slices and the preferred number of nearest neighbours. \
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Only type in Greek, with correct spirits and accents
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)
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target_word = st.multiselect("Enter a word", options=all_models_words, max_selections=1)
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if len(target_word) > 0:
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@@ -207,7 +207,7 @@ if selected == "App":
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'Here you can extract the cosine similarity between two lemmas. \
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Please select a time slice for each lemma. \
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You can also calculate the cosine similarity between two vectors of the same lemma in different time slices. \
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Only type in Greek, with correct spirits and accents
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)
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col1, col2 = st.columns(2)
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col3, col4 = st.columns(2)
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@@ -244,7 +244,7 @@ if selected == "App":
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st.markdown("## 3D graph")
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st.markdown('''
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Here you can generate a 3D representation of the semantic space surrounding a target lemma. Please choose the lemma and the time slice.\
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Only type in Greek, with correct spirits and accents
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**NB**: the 3D representations are reductions of the multi-dimensional representations created by the models. \
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@@ -289,7 +289,7 @@ if selected == "App":
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with st.container():
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st.markdown('## Dictionary')
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st.markdown('Search a word in the Liddell-Scott-Jones dictionary. Only type in Greek, with correct spirits and accents
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all_lemmas = load_all_lemmas()
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st.markdown(
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'Here you can extract the nearest neighbours to a chosen lemma. \
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Please select one or more time slices and the preferred number of nearest neighbours. \
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**Only type in Greek, with correct spirits and accents**.'
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)
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target_word = st.multiselect("Enter a word", options=all_models_words, max_selections=1)
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if len(target_word) > 0:
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'Here you can extract the cosine similarity between two lemmas. \
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Please select a time slice for each lemma. \
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You can also calculate the cosine similarity between two vectors of the same lemma in different time slices. \
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210 |
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**Only type in Greek, with correct spirits and accents**. '
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)
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col1, col2 = st.columns(2)
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col3, col4 = st.columns(2)
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st.markdown("## 3D graph")
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st.markdown('''
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Here you can generate a 3D representation of the semantic space surrounding a target lemma. Please choose the lemma and the time slice.\
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+
**Only type in Greek, with correct spirits and accents**. \
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**NB**: the 3D representations are reductions of the multi-dimensional representations created by the models. \
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with st.container():
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st.markdown('## Dictionary')
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st.markdown('Search a word in the Liddell-Scott-Jones dictionary. **Only type in Greek, with correct spirits and accents**. ')
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all_lemmas = load_all_lemmas()
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