Update space.py

space.py

@@ -1,22 +1,16 @@
 import gradio as gr
-from gradio_leaderboard import Leaderboard, SelectColumns
+from gradio_leaderboard import Leaderboard, SelectColumns, ColumnFilter
 import config
 from pathlib import Path
 import pandas as pd
+import random
 
 abs_path = Path(__file__).parent
 
 df = pd.read_json(str(abs_path / "leaderboard_data.json"))
-
-# Make a model size column
-numeric_interval = pd.IntervalIndex(
-    sorted([config.NUMERIC_INTERVALS[s] for s in config.NUMERIC_INTERVALS.keys()])
-)
-params_column = pd.to_numeric(df["#Params (B)"], errors="coerce")
-df["Model Size"] = params_column.apply(
-    lambda x: next(s for s in numeric_interval if x in s)
-)
-
+# Randomly set True/ False for the "MOE" column
+df["MOE"] = [random.random() > 0.5 for _ in range(len(df))]
+df["Flagged"] = [random.random() > 0.5 for _ in range(len(df))]
 
 with gr.Blocks() as demo:
     gr.Markdown("""
@@ -33,8 +27,15 @@ with gr.Blocks() as demo:
                 ),
                 search_columns=["model_name_for_query", "Type"],
                 hide_columns=["model_name_for_query", "Model Size"],
-                filter_columns=config.FILTER_COLUMNS,
+                filter_columns=[
+                    "T",
+                    "Precision",
+                    ColumnFilter("MOE", type="checkbox", default=False, label="MoE"),
+                    ColumnFilter("Flagged", type="checkbox", default=False),
+                    ColumnFilter("#Params (B)", default=[30, 80]),
+                ],
                 datatype=config.TYPES,
+                column_widths=["2%", "33%"],
             )
         with gr.Tab("Docs"):
             gr.Markdown((Path(__file__).parent / "docs.md").read_text())