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Added blog post "PyTorch Docathon H2 2023 Wrap-up"
Signed-off-by: Chris Abraham <cjyabraham@gmail.com>
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title: "🎉 PyTorch Docathon H2 2023 Wrap-up 🎉"
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We are thrilled to announce the successful completion of the Fall 2023 PyTorch Docathon! The event was a resounding success, and we want to extend our heartfelt gratitude to all the participants who made it possible. Dedication, expertise, and tireless efforts of our open-source contributors have once again helped us to improve PyTorch documentation.
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This Docathon ran from Nov 1 through Nov 15 with more than 170 registrants. The energy and enthusiasm were palpable, and entrants were judged on the difficulty of submissions that resulted in over TBA merged pull requests. We have fixed the PyTorch docstrings and made them compatible with the PEP 257 Python Docstring Conventions guidelines. We also have fixed multiple bugs in the pytorch/tutorials repo.
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We want to give a special shout-out to our top contributors, who went above and beyond during this event. Your dedication and expertise have been invaluable in enhancing the PyTorch documentation and empowering developers worldwide.
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Meet the top contributors:
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- First place: [ahoblitz](https://github.com/ahoblitz), [spzala](https://github.com/spzala), [alperenunlu](https://github.com/alperenunlu), [ChanBong](https://github.com/ChanBong)
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- Second place: [nvs-abhilash](https://github.com/nvs-abhilash), [bjhargrave](https://github.com/bjhargrave), [zabboud](https://github.com/zabboud)
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- Third place: [guptaaryan16](https://github.com/guptaaryan16), [min-jean-cho](https://github.com/min-jean-cho), [markstur](https://github.com/markstur)
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- Honorable mentions: [RustyGrackle](https://github.com/RustyGrackle), [Viditagarwal7479](https://github.com/Viditagarwal7479), [Skylion007](https://github.com/Skylion007)
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You can see the full docathon leaderboard published [here](https://github.com/pytorch/tutorials/blob/main/docathon-leaderboard.md).
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As we bring this Docathon to a close, we encourage each and every one of you to stay inspired and keep contributing to PyTorch documentation and code, and pushing the boundaries of what's possible with PyTorch. Your collective efforts are shaping the landscape of deep learning and fostering innovation in the PyTorch community.
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Thank you again for your participation and support. We look forward to seeing what you will achieve next!
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Team PyTorch

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