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Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -750,7 +750,7 @@ with gr.Blocks(css=css_tech_theme) as demo:
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  <li>1️⃣ <strong>Download the Dataset:</strong> Access the dataset and detailed instructions on the <a href="https://github.com/VILA-Lab/Mobile-MMLU" target="_blank">GitHub page</a>. Follow the steps to ensure your environment is set up correctly.</li>
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  <li>2️⃣ <strong>Generate Predictions:</strong> Use the provided script in the GitHub repository to generate answers. Ensure the output file matches the format in the github </li>
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  <li>3️⃣ <strong>Submit Predictions:</strong> Upload your CSV file to the <strong>Submission Page</strong> on this platform.</li>
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- <li>4️⃣ <strong>Evaluation:</strong> Your submission will be scored based on accuracy. The results will include overall and valid accuracy metrics.</li>
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  <li>5️⃣ <strong>Leaderboard:</strong> Optionally, add your results to the real-time leaderboard to compare your model's performance with others.</li>
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  </ol>
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  <h3 style="color: #8e44ad;">Resources</h3>
 
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  <li>1️⃣ <strong>Download the Dataset:</strong> Access the dataset and detailed instructions on the <a href="https://github.com/VILA-Lab/Mobile-MMLU" target="_blank">GitHub page</a>. Follow the steps to ensure your environment is set up correctly.</li>
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  <li>2️⃣ <strong>Generate Predictions:</strong> Use the provided script in the GitHub repository to generate answers. Ensure the output file matches the format in the github </li>
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  <li>3️⃣ <strong>Submit Predictions:</strong> Upload your CSV file to the <strong>Submission Page</strong> on this platform.</li>
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+ <li>4️⃣ <strong>Evaluation:</strong> Your submission will be scored based on accuracy. The results will include overall accuracy metric.</li>
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  <li>5️⃣ <strong>Leaderboard:</strong> Optionally, add your results to the real-time leaderboard to compare your model's performance with others.</li>
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  </ol>
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  <h3 style="color: #8e44ad;">Resources</h3>