n-shot filter

app.py

@@ -24,7 +24,8 @@ from src.display.utils import (
     ModelType,
     fields,
     WeightType,
-    Precision
+    Precision,
+    NShotType,
 )
 from src.envs import API, DEVICE, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REPO_ID, RESULTS_REPO, TOKEN
 from src.populate import get_evaluation_queue_df, get_leaderboard_df
@@ -199,6 +200,13 @@ with demo:
                         interactive=True,
                         elem_id="filter-columns-size",
                     )
+                    filter_columns_nshot = gr.CheckboxGroup(
+                        label="N-shot",
+                        choices=[i.value.name for i in NShotType],
+                        value=[i.value.name for i in NShotType],
+                        interactive=True,
+                        elem_id="filter-columns-nshot",
+                    )
 
             leaderboard_table = gr.components.Dataframe(
                 value=leaderboard_df[

src/display/utils.py

@@ -26,6 +26,7 @@ auto_eval_column_dict = []
 # Init
 auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
 auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
+auto_eval_column_dict.append(["n_shot", ColumnContent, ColumnContent("n_shot", "number", True)])
 #Scores
 auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "number", True)])
 for task in Tasks:
@@ -40,7 +41,6 @@ auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B
 auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
 auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
 auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
-auto_eval_column_dict.append(["n_shot", ColumnContent, ColumnContent("n_shot", "number", False)])
 # Dummy column for the search bar (hidden by the custom CSS)
 auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("model_name_for_query", "str", False, dummy=True)])
 
@@ -92,6 +92,10 @@ class WeightType(Enum):
     Original = ModelDetails("Original")
     Delta = ModelDetails("Delta")
 
+class NShotType(Enum):
+    n0 = ModelDetails("0")
+    n5 = ModelDetails("5")
+
 class Precision(Enum):
     float16 = ModelDetails("float16")
     bfloat16 = ModelDetails("bfloat16")