Update app.py

app.py

@@ -4,12 +4,7 @@ import pandas as pd
 banner_url = "https://huggingface.co/spaces/elmresearchcenter/open_universal_arabic_asr_leaderboard/resolve/main/banner.png"
 BANNER = f'<div style="display: flex; justify-content: space-around;"><img src="{banner_url}" alt="Banner" style="width: 7vw; min-width: 300px; max-width: 600px;"> </div>'
 
-INTRODUCTION_TEXT = """
-📖**Open Universal Arabic ASR Leaderboard**📖 benchmarks multi-dialect Arabic ASR models on various multi-dialect datasets.
-\nApart from the WER%/CER% for each test set, we also report the Average WER%/CER% and rank the models based on the Average WER, from lowest to highest.
-\nTo reproduce the benchmark numbers and request a model that is not listed, you can launch an issue/PR in our [GitHub repo](https://github.com/Natural-Language-Processing-Elm/open_universal_arabic_asr_leaderboard)😊.
-\nFor more detailed analysis such as models' robustness, speaker adaption, model efficiency and memory usage, please check our [paper](https://arxiv.org/pdf/2412.13788).
-"""
+INTRODUCTION_TEXT = "📖**Open Universal Arabic ASR Leaderboard**📖 benchmarks multi-dialect Arabic ASR models on various multi-dialect datasets.<br>Apart from the WER%/CER% for each test set, we also report the Average WER%/CER% and rank the models based on the Average WER, from lowest to highest.<br>To reproduce the benchmark numbers and request a model that is not listed, you can launch an issue/PR in our [GitHub repo](https://github.com/Natural-Language-Processing-Elm/open_universal_arabic_asr_leaderboard)😊.<br>For more detailed analysis such as models' robustness, speaker adaption, model efficiency and memory usage, please check our [paper](https://arxiv.org/pdf/2412.13788)."
 
 CITATION_BUTTON_TEXT = """
 @article{wang2024open,