Update README.md

README.md

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 <h2>Where does the community live in?</h2>
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-👾 hf-fastai channel in the <a href="https://discord.gg/eXgFp5FRsz">fast.ai Discord server</a>
+<p>👾 hf-fastai channel in the <a href="https://discord.gg/eXgFp5FRsz">fast.ai Discord server</a></p>
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-❤️ Check out <a href="https://huggingface.co/spaces/hugginglearners/Hearts_Leaderboard">leaderboard</a> with the most liked Spaces
+<p>❤️ Check out <a href="https://huggingface.co/spaces/hugginglearners/Hearts_Leaderboard">leaderboard</a> with the most liked Spaces</p>
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-💝 To get started with the sprint, check out <a href="https://huggingface2.notion.site/fast-ai-x-Sprint-76bf3524c6194740a4cdf657f59e45f3" title="Optional Title">this page</a> containing end-to-end workflow we expect and tutorials.
+<p>💝 To get started with the sprint, check out <a href="https://huggingface2.notion.site/fast-ai-x-Sprint-76bf3524c6194740a4cdf657f59e45f3" title="Optional Title">this page</a> containing end-to-end workflow we expect and tutorials.</p>
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 <h2>Who are we?</h2>
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-Group to share Vision and Text pre-trained fastai Learners with the community for further community usage and reproducibility.
+<p>Group to share Vision and Text pre-trained fastai Learners with the community for further community usage and reproducibility.</p>
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 <h2>What are we doing?</h2>
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-We're training fast.ai models, building demos to them and share them. We believe in openly sharing knowledge and resources to democratize AI for all. At Hugging Face, we encourage all practitioners who train models to contribute by sharing them with the community. Even when trained on particular data sets, sharing Learners will help others save time and computing resources, and give them access to valuable trained artifacts. In turn, you can benefit from the work that others have done. Additionally, shared Learners can be replicated by other community members through, for example, the inference API or repository cloning. 
+<p>We're training fast.ai models, building demos to them and share them. We believe in openly sharing knowledge and resources to democratize AI for all. At Hugging Face, we encourage all practitioners who train models to contribute by sharing them with the community. Even when trained on particular data sets, sharing Learners will help others save time and computing resources, and give them access to valuable trained artifacts. In turn, you can benefit from the work that others have done. Additionally, shared Learners can be replicated by other community members through, for example, the inference API or repository cloning. </p>
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 <h2>Do you have questions? 🤗 </h2>
-Please ask in the hf-fastai channel in the [fast.ai Discord](https://discord.gg/eXgFp5FRsz).
+<p>Please ask in the hf-fastai channel in the [fast.ai Discord](https://discord.gg/eXgFp5FRsz).</p>
    
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 <h2> Relevant links 🔗 </h2>
-- Here is a <a href="https://colab.research.google.com/github/huggingface/blog/blob/main/notebooks/64_fastai_hub.ipynb">notebook</a> on how to share and load fastai Learners to and from the Hugging Face Hub, including Learners using blurr.
-- Hugging Face documentation on <a href="https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.from_pretrained_fastai">fast.ai</a>
+<p>📓 Here is a <a href="https://colab.research.google.com/github/huggingface/blog/blob/main/notebooks/64_fastai_hub.ipynb">notebook</a> on how to share and load fastai Learners to and from the Hugging Face Hub, including Learners using blurr.</p>
+<p> 📚 Hugging Face documentation on <a href="https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.from_pretrained_fastai">fast.ai</a></p>
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