Update app.py
Browse files
app.py
CHANGED
@@ -16,13 +16,13 @@ Additionally, the model was tasked with finding the topic of each cluster.
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""")
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@st.cache_data
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def load_data(
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ds = load_dataset("HuggingFaceTB/FW_clusters_free_topics", split="train", token=HF_TOKEN, num_proc=2)
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ds = ds.filter(lambda x: x['educational_score'] <= max_score and x['educational_score'] >= min_score)
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return ds
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-
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st.subheader("Cluster information")
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min_score, max_score = st.columns(2)
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with min_score:
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min_value = st.slider('Select minimum educational score', 1, 10, 1)
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@@ -31,9 +31,6 @@ with max_score:
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ds = load_data(educational_topic, min_score, max_score)
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categories = list(set(ds["category"]))
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selected_category_type = st.selectbox("Select a topic", categories)
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selected_cluster = ds.filter(lambda x: x['category'] == selected_category)
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# Select sample index
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""")
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@st.cache_data
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def load_data(min_score=1, max_score=10):
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ds = load_dataset("HuggingFaceTB/FW_clusters_free_topics", split="train", token=HF_TOKEN, num_proc=2)
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ds = ds.filter(lambda x: x['educational_score'] <= max_score and x['educational_score'] >= min_score)
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return ds
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st.subheader("Cluster information")
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selected_category_type = st.selectbox("Select a topic", categories)
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min_score, max_score = st.columns(2)
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with min_score:
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min_value = st.slider('Select minimum educational score', 1, 10, 1)
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ds = load_data(educational_topic, min_score, max_score)
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categories = list(set(ds["category"]))
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selected_cluster = ds.filter(lambda x: x['category'] == selected_category)
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# Select sample index
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