4

app.py

@@ -86,7 +86,7 @@ def init_leaderboard(dataframe):
                 label="Select the number of parameters (B)",
             ),
             ColumnFilter(
-                AutoEvalColumn.still_on_hub.name, type="boolean", label="Closed-source", default=True
+                AutoEvalColumn.still_on_hub.name, type="boolean", label="Available on the hub", default=False
             ),
         ],
         bool_checkboxgroup_label="Hide models",

src/about.py

@@ -27,50 +27,17 @@ NUM_FEWSHOT = 0 # Change with your few shot
 #TODO title
 TITLE = """<h1 align="center" id="space-title">VLM Detailed Caption Leaderborad</h1>"""
 
-
-
-#TODO interoduction
+# introduction text
 INTRODUCTION_TEXT = """
     <div style="display: flex; flex-wrap: wrap; gap: 10px;">
-        <!-- Release badge -->
-        <a href="https://github.com/yanchenyang123/DeepSeek-V3/releases" target="_blank">
-            <img src="https://img.shields.io/github/v/release/yanchenyang123/DeepSeek-V3?style=flat-square" alt="release">
-        </a>
-        <!-- Docker badge -->
-        <a href="https://hub.docker.com/r/your-docker-image" target="_blank">
-            <img src="https://img.shields.io/badge/docker-v1.3.1-blue?style=flat-square" alt="docker">
-        </a>
-        <!-- Stars badge -->
-        <a href="https://github.com/yanchenyang123/DeepSeek-V3/stargazers" target="_blank">
-            <img src="https://img.shields.io/github/stars/yanchenyang123/DeepSeek-V3?style=flat-square" alt="stars">
-        </a>
-        <!-- Issues badge -->
+        
+        <!-- Paper badge with custom icon -->
         <a href="https://github.com/yanchenyang123/DeepSeek-V3/issues" target="_blank">
-            <img src="https://img.shields.io/github/issues/yanchenyang123/DeepSeek-V3?color=pink&style=flat-square" alt="issues">
-        </a>
-        <!-- Contributors badge -->
-        <a href="https://github.com/yanchenyang123/DeepSeek-V3/graphs/contributors" target="_blank">
-            <img src="https://img.shields.io/github/contributors/yanchenyang123/DeepSeek-V3?color=yellowgreen&style=flat-square" alt="contributors">
-        </a>
-        <!-- Forks badge -->
-        <a href="https://github.com/yanchenyang123/DeepSeek-V3/network/members" target="_blank">
-            <img src="https://img.shields.io/github/forks/yanchenyang123/DeepSeek-V3?color=cyan&style=flat-square" alt="forks">
-        </a>
-        <!-- License badge -->
-        <a href="https://github.com/yanchenyang123/DeepSeek-V3/blob/main/LICENSE" target="_blank">
-            <img src="https://img.shields.io/github/license/yanchenyang123/DeepSeek-V3?color=black&style=flat-square" alt="license">
-        </a>
-        <!-- WeChat badge -->
-        <a href="https://your-wechat-link.com" target="_blank">
-            <img src="https://img.shields.io/badge/WeChat-微信-green?style=flat-square" alt="WeChat">
-        </a>
-        <!-- Hugging Face Spaces badge -->
-        <a href="https://huggingface.co/spaces/your-space" target="_blank">
-            <img src="https://img.shields.io/badge/Open%20in%20Spaces-%F0%9F%A4%AF-orange?style=flat-square" alt="Open in Spaces">
+            <img src="https://img.shields.io/badge/Paper-Available-blue?style=flat-square&logo=book&logoColor=white" alt="Paper">
         </a>
+
     </div>
     """
-
 #TODO About
 LLM_BENCHMARKS_TEXT = f"""
 <h2 style="color: #2c3e50;"> Why Leaderboard? </h2>

src/display/utils.py

@@ -24,22 +24,22 @@ class ColumnContent:
 auto_eval_column_dict = []
 #TODO
 # Init
-auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
+#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)])
 # #Scores
 # auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "number", True)])
 for task in Tasks:
-    auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "float", True)])
+    auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "float", True , never_hidden= True)])
 # Model information
-auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
-auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
-auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
-auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
-auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
-auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "float", False)])
-auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
+#auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
+#auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
+#auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
+#auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
+#auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
+#auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "float", False)])
+#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(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
 
 # We use make dataclass to dynamically fill the scores from Tasks
 AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)

src/leaderboard/read_evals.py

@@ -115,17 +115,17 @@ class EvalResult:
         #average = next(iter(self.results.values()))
         data_dict = {
             "eval_name": self.eval_name,  # not a column, just a save name,
-            AutoEvalColumn.precision.name: self.precision.value.name,   #results/precision
-            AutoEvalColumn.model_type.name: self.model_type.value.name,  #requests/model_type
-            AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
-            AutoEvalColumn.weight_type.name: self.weight_type.value.name,
-            AutoEvalColumn.architecture.name: self.architecture,
+            #AutoEvalColumn.precision.name: self.precision.value.name,   #results/precision
+            #AutoEvalColumn.model_type.name: self.model_type.value.name,  #requests/model_type
+            #AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
+            #AutoEvalColumn.weight_type.name: self.weight_type.value.name,
+            #AutoEvalColumn.architecture.name: self.architecture,
             AutoEvalColumn.model.name: make_clickable_model(self.full_model),
-            AutoEvalColumn.revision.name: self.revision,
+            #AutoEvalColumn.revision.name: self.revision,
             #AutoEvalColumn.average.name: average,
-            AutoEvalColumn.license.name: self.license,
-            AutoEvalColumn.likes.name: self.likes,
-            AutoEvalColumn.params.name: self.num_params,
+            #AutoEvalColumn.license.name: self.license,
+            #AutoEvalColumn.likes.name: self.likes,
+            #AutoEvalColumn.params.name: self.num_params,
             AutoEvalColumn.still_on_hub.name: self.still_on_hub,
         }