update model size filter.

app.py

@@ -23,6 +23,7 @@ from src.display.utils import (
     EVAL_COLS,
     EVAL_TYPES,
     NUMERIC_INTERVALS,
+    NUMERIC_MODELSIZE,
     TYPES,
     AutoEvalColumn,
     GroupDtype,
@@ -203,8 +204,8 @@ def filter_models(
     mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
     filtered_df = filtered_df.loc[mask]
 
-    numeric_interval_params = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in params_query]))
-    params_column_params = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
+    numeric_interval_params = pd.IntervalIndex(sorted([NUMERIC_MODELSIZE[s] for s in params_query]))
+    params_column_params = pd.to_numeric(df[AutoEvalColumn.model_size.name], errors="coerce")
     mask_params = params_column_params.apply(lambda x: any(numeric_interval_params.contains(x)))
     filtered_df = filtered_df.loc[mask_params]
 
@@ -214,7 +215,7 @@ leaderboard_df = filter_models(
     df=leaderboard_df, 
     type_query=[t.to_str(" : ") for t in QuantType], 
     size_query=list(NUMERIC_INTERVALS.keys()), 
-    params_query=list(NUMERIC_INTERVALS.keys()),
+    params_query=list(NUMERIC_MODELSIZE.keys()),
     precision_query=[i.value.name for i in Precision],
     hide_models=["Private or deleted", "Contains a merge/moerge", "Flagged"], # Deleted, merges, flagged, MoEs,
     compute_dtype=[i.value.name for i in ComputeDtype],
@@ -266,8 +267,8 @@ with demo:
                     with gr.Row():
                         filter_columns_size = gr.CheckboxGroup(
                         label="Model sizes (GB, int4)",
-                        choices=list(NUMERIC_INTERVALS.keys()),
-                        value=list(NUMERIC_INTERVALS.keys()),
+                        choices=list(NUMERIC_MODELSIZE.keys()),
+                        value=list(NUMERIC_MODELSIZE.keys()),
                         interactive=True,
                         elem_id="filter-columns-size",
                     )
@@ -333,8 +334,8 @@ with demo:
                     shown_columns,
                     filter_columns_type,
                     filter_columns_precision,
-                    filter_columns_size,
                     filter_columns_parameters,
+                    filter_columns_size,
                     hide_models,
                     search_bar,
                     filter_columns_computeDtype,
@@ -377,8 +378,8 @@ with demo:
                         shown_columns,
                         filter_columns_type,
                         filter_columns_precision,
-                        filter_columns_size,
                         filter_columns_parameters,
+                        filter_columns_size,
                         hide_models,
                         search_bar,
                         filter_columns_computeDtype,

src/display/utils.py

@@ -208,7 +208,7 @@ class QuantType(Enum):
     awq = ModelDetails(name="AWQ", symbol="🟩")
     llama_cpp = ModelDetails(name="llama.cpp", symbol="🔶")
     bnb = ModelDetails(name="bitsandbytes", symbol="💬")
-    autoround = ModelDetails(name="AutoRound", symbol="🌐")
+    autoround = ModelDetails(name="AutoRound", symbol="🍒")
     Unknown = ModelDetails(name="?", symbol="?")
 
     def to_str(self, separator=" "):
@@ -343,3 +343,11 @@ NUMERIC_INTERVALS = {
     # "~60": pd.Interval(45, 70, closed="right"),
     # "70+": pd.Interval(70, 10000, closed="right"),
 }
+
+NUMERIC_MODELSIZE = {
+    "?": pd.Interval(-1, 0, closed="right"),
+    "~4": pd.Interval(0, 4, closed="right"),
+    "~8": pd.Interval(4, 8, closed="right"),
+    "~16": pd.Interval(8, 16, closed="right"),
+    "~36": pd.Interval(16, 36, closed="right"),
+}