Update README.md

README.md

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    <img class="lg:col-span-2" src="https://huggingface.co/spaces/Gradio-Blocks/README/resolve/main/banner.png" alt="Gradio Banner" style="margin:10px">
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-    We are happy to invite you to the Gradio Blocks Party - a community event in which we will create <b>interactive demos</b> for state-of-the-art machine learning models. Demos are powerful because they allow anyone — not just ML engineers — to try out models in the browser, give feedback on predictions, identify trustworthy models. The event will take place from May 16th to 31st. We will be organizing this event on <a href="https://github.com/huggingface/community-events" target="_blank" style="text-decoration: underline">Github</a> and the <a href="https://discord.com/invite/feTf9x3ZSB" target="_blank" style="text-decoration: underline">Hugging Face discord channel</a>. Prizes will be given at the end of the event, see: <a href="#Prizes" target="_blank" style="text-decoration: underline">Prizes</a> </p><br />
+    We are happy to invite you to the Gradio Blocks Party - a community event in which we will create <b>interactive demos</b> for state-of-the-art machine learning models. Demos are powerful because they allow anyone — not just ML engineers — to try out models in the browser, give feedback on predictions, identify trustworthy models. The event will take place from <b>May 16th to 31st</b>. We will be organizing this event on <a href="https://github.com/huggingface/community-events" target="_blank" style="text-decoration: underline">Github</a> and the <a href="https://discord.com/invite/feTf9x3ZSB" target="_blank" style="text-decoration: underline">Hugging Face discord channel</a>. Prizes will be given at the end of the event, see the <a href="#Prizes" target="_blank" style="text-decoration: underline">Prizes section</a> </p><br />
    
-   <p class="lg:col-span-2"> We will be building demos using the new Gradio Blocks API. Blocks allows you to build web-based demos in a flexible way using the <a href="https://www.gradio.app">Gradio library</a>. Gradio is a popular choice for building demos for machine learning models, as it allows you to create UIs from Python. For example, here is a UI for Dall-E Mini using Gradio Blocks:
+   <p class="lg:col-span-2"> We will be building demos using the new Gradio Blocks API. Blocks allows you to build web-based demos in a flexible way using the <a href="https://www.gradio.app">Gradio library</a>. Gradio is a popular choice for building demos for machine learning models, as it allows you to create web-based UIs all in Python. For example, here is a UI for Dall-E Mini using Gradio Blocks:
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-   <h3  class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">What is Gradio?</h3>
+   <h3  class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">More About Gradio</h3>
    <p class="lg:col-span-2">
      Gradio is a Python library that allows you to quickly build web-based machine learning demos, data science dashboards, or other kinds of web apps, entirely in Python. These web apps can be launched from wherever you use Python (jupyter notebooks, colab notebooks, Python terminal, etc.) and shared with anyone instantly using Gradio's auto-generated share links. To learn more about Gradio see the Getting Started Guide:  <a href="https://gradio.app/getting_started/" target="_blank" style="text-decoration: underline">https://gradio.app/getting_started/</a> and the new Course on Huggingface about Gradio:  <a href="https://huggingface.co/course/chapter9/1?fw=pt" style="text-decoration: underline" target="_blank">Gradio Course</a>.
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    <p class="lg:col-span-2"><code>pip install gradio</code> to install gradio locally</p>
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-   <h3  class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">What is Blocks?</h3>
+   <h3  class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">Gradio Blocks</h3>
    <p class="lg:col-span-2">
      <code>gradio.Blocks</code> is a low-level API that allows you to have full control over the data flows and layout of your application. You can build very complex, multi-step applications using Blocks.
      If you have already used gradio.Interface, you know that you can easily create fully-fledged machine learning demos with just a few lines of code. The Interface API is very convenient but in some cases may not be sufficiently flexible for your needs. For example, you might want to:
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    <li class="my-4">1st place winner based on likes<ul class="lg:col-span-2" style="list-style: circle inside;padding-left: 40px;">
    <li class="my-4"><a href="https://huggingface.co/pricing">Hugging Face PRO subscription</a> for 1 year</li>
    <li class="my-4">Embedding your Gradio Blocks demo in the Gradio Blog</li>
+   <li class="my-4">Gradio Team Office Hour</li>
    </ul>
    </li>
    <li class="my-4">top 10 winners based on likes<ul class="lg:col-span-2" style="list-style: circle inside;padding-left: 40px;">