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title: "️✔️Summary" | ||
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# ✔️Summary | ||
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<h3 align="justify"> | ||
Nowadays, Big Tech corporations are training state of the art multi-billion parameter models on thousands of GPUs, | ||
spending millions of dollars on it, which the ordinary researcher cannot afford. 😢 | ||
<br><br> | ||
What I want to show with this project is that even for a non-profit research task, you can find like-minded | ||
volunteers and train a fairly large machine learning model. | ||
</h3> | ||
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## Work accomplished | ||
- <div align="justify"><font size="4">Designed and trained 50M parameters Transformer model to “read” meaningful text in columns that can be compiled for a | ||
<a href="https://en.wikipedia.org/wiki/Running_key_cipher">Running Key Cipher</a>, widely known in field of Cryptography</font></div> | ||
- <div align="justify"><font size="4">Implemented the code base and prepared the infrastructure for conveniently conducting an experiment on | ||
distributed model training across the Internet with the help of volunteers</font></div> | ||
- <div align="justify"><font size="4">Implemented beam search for inference and CLI interface, dashboard and API with a | ||
celery worker under the hood for convenient interaction, and packed it all into docker to make it more reproducible</font></div> | ||
- <div align="justify"><font size="4">Configured CI/CD pipelines to publish python package to PyPi, build docker images | ||
and push them to Docker Hub and GitHub Packages, sync repository with HuggingFace Sphere and update project website</font></div> |
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