close by default

app.py

@@ -39,12 +39,14 @@ df = pd.DataFrame(
 ).reset_index()
 df_with_org = df.copy(deep=True)
 
+
 def parse_org(hub_id):
-    parts = hub_id.split('/')
+    parts = hub_id.split("/")
     return parts[0] if len(parts) == 2 else None
 
+
 df_with_org["org"] = df_with_org["base_model"].apply(parse_org)
-df_with_org = df_with_org.dropna(subset=['org'])
+df_with_org = df_with_org.dropna(subset=["org"])
 
 grouped_by_base_model = groupby(
     lambda x: x.cardData.get("base_model"), models_with_base_model_info
@@ -79,16 +81,17 @@ with gr.Blocks() as demo:
     base_model = gr.Dropdown(all_base_models, label="Base Model")
     results = gr.Markdown()
     base_model.change(return_models_for_base_model, base_model, results)
-    with gr.Accordion("Base model popularity ranking"):
+    with gr.Accordion("Base model popularity ranking", open=False):
         gr.DataFrame(df.head(50))
-    with gr.Accordion("Base model popularity ranking by organisation"):
+    with gr.Accordion("Base model popularity ranking by organisation", open=False):
         gr.DataFrame(
             pd.DataFrame(
-            df_with_org.groupby("org")["count"]
-            .sum()
-            .sort_values(ascending=False)
-            .head(50)
-        ).reset_index()).sort_values("count", ascending=False)
+                df_with_org.groupby("org")["count"]
+                .sum()
+                .sort_values(ascending=False)
+                .head(50)
+            ).reset_index()
+        ).sort_values("count", ascending=False)
 
 
 demo.launch()