feat: Add allow_custom_value option to base_model dropdown

app.py

@@ -49,7 +49,6 @@ df = pd.DataFrame(
 df_with_org = df.copy(deep=True)
 pipeline_tags = [x.pipeline_tag for x in models_with_base_model_info]
 # sort pipeline tags alphabetically
-pipeline_tags = sorted(pipeline_tags)
 unique_pipeline_tags = list(
     {x.pipeline_tag for x in models_with_base_model_info if x.pipeline_tag is not None}
 )
@@ -74,7 +73,7 @@ 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
 )
-
+print(df.columns)
 all_base_models = df["base_model"].to_list()
 
 
@@ -178,7 +177,7 @@ with gr.Blocks() as demo:
 
     gr.Markdown(produce_summary())
     gr.Markdown("## Find all models trained from a base model")
-    base_model = gr.Dropdown(all_base_models, label="Base Model")
+    base_model = gr.Dropdown(all_base_models, label="Base Model",allow_custom_value=True)
     results = gr.Markdown()
     base_model.change(return_models_for_base_model, base_model, results)
     gr.Markdown("## Base model rankings ")