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Update app.py
Browse files
app.py
CHANGED
@@ -13,6 +13,7 @@ with st.spinner("π load language model (sentence transformer)"):
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with st.spinner("π load sdg data"):
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df_osdg = pd.read_csv('https://zenodo.org/record/5550238/files/osdg-community-dataset-v21-09-30.csv',sep='\t')
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_lab_dict = {0: 'no_cat',
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1:'SDG 1 - No poverty',
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@@ -38,7 +39,7 @@ with st.spinner("π load sdg data"):
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docs = list(df_osdg['text'])
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docs_embeddings = model.encode(docs)
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with st.spinner("π
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n_neighbors = 15
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n_components = 3
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random_state =42
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@@ -49,7 +50,8 @@ with st.spinner("π create visualisation"):
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.fit(docs_embeddings))
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docs_umap = umap_model.transform(docs_embeddings)
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fig = px.scatter_3d(
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docs_umap, x=0, y=1, z=2,
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color=labels,
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with st.spinner("π load sdg data"):
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df_osdg = pd.read_csv('https://zenodo.org/record/5550238/files/osdg-community-dataset-v21-09-30.csv',sep='\t')
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df_osdg = df_osdg[:1000]
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_lab_dict = {0: 'no_cat',
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1:'SDG 1 - No poverty',
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docs = list(df_osdg['text'])
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docs_embeddings = model.encode(docs)
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with st.spinner("π prepare visualisation"):
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n_neighbors = 15
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n_components = 3
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random_state =42
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.fit(docs_embeddings))
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docs_umap = umap_model.transform(docs_embeddings)
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with st.spinner("π create visualisation"):
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fig = px.scatter_3d(
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docs_umap, x=0, y=1, z=2,
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color=labels,
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