keep only multimodal tab

app.py

@@ -67,45 +67,7 @@ with hf_app:
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
 
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
-        """
-        #######################        FIRST TAB - TEXT-LEADERBOARD       #######################
-        """
-        with gr.TabItem(TEXT_NAME, elem_id="llm-benchmark-tab-table", id=0):
-            with gr.Row():
-                search_bar = gr.Textbox(
-                    placeholder=" 🔍 Search for models - separate multiple queries with `;` and press ENTER...",
-                    show_label=False,
-                    elem_id="search-bar",
-                )
-
-            leaderboard_table = gr.Dataframe(
-                value=text_leaderboard,
-                elem_id="text-leaderboard-table",
-                interactive=False,
-                visible=True,
-                height=dataframe_height
-            )
-
-            # Show information about the clemscore and last updated date below the table
-            gr.HTML(CLEMSCORE_TEXT)
-            gr.HTML(f"Last updated - {github_data['date']}")
 
-            # Add a dummy leaderboard to handle search queries in leaderboard_table
-            # This will show a temporary leaderboard based on the searched value
-            dummy_leaderboard_table = gr.Dataframe(
-                value=text_leaderboard,
-                elem_id="text-leaderboard-table-dummy",
-                interactive=False,
-                visible=False
-            )
-
-            # Action after submitting a query to the search bar
-            search_bar.submit(
-                query_search,
-                [dummy_leaderboard_table, search_bar],
-                leaderboard_table,
-                queue=True
-            )
 
         """
         #######################       SECOND TAB - MULTIMODAL LEADERBOARD     #######################

src/assets/text_content.py

@@ -1,4 +1,4 @@
-TITLE = """<h1 align="center" id="space-title"> 🏆 CLEM Leaderboard</h1>"""
+TITLE = """<h1 align="center" id="space-title"> 🏆 Multimodal CLEM Leaderboard</h1>"""
 
 REPO = "https://raw.githubusercontent.com/clembench/clembench-runs/main/"
 HF_REPO = "colab-potsdam/clem-leaderboard"
@@ -11,10 +11,10 @@ INTRODUCTION_TEXT = """
 
 The CLEM Leaderboard aims to track, rank and evaluate current cLLMs (chat-optimized Large Language Models) with the suggested pronounciation “clems”. 
 
-The benchmarking approach is described in [Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents](https://aclanthology.org/2023.emnlp-main.689.pdf).
-
 The multimodal benchmark is described in [Two Giraffes in a Dirt Field: Using Game Play to Investigate Situation Modelling in Large Multimodal Models](https://arxiv.org/abs/2406.14035)
 
+The original benchmarking approach for text-only models is described in [Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents](https://aclanthology.org/2023.emnlp-main.689.pdf).
+
 Source code for benchmarking "clems" is available here: [Clembench](https://github.com/clembench/clembench)
 
 All generated files and results from the benchmark runs are available here: [clembench-runs](https://github.com/clembench/clembench-runs) </h6>