Contributing
This project welcomes contributions and suggestions. Most contributions require you to
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This project welcomes contributions and suggestions. Most contributions require you to
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Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet
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[](https://arxiv.org/abs/2303.17580)
*.dev.yaml
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
1. Fork the repository you want to contribute to by clicking the "Fork" button on the project page.
This repository contains the code for developing, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book [Build a Large Language Model (From Scratch)](https://amzn.to/4fqvn0D).
path = reasoning-from-scratch
reports/

.idea
*.ipynb linguist-generated
LLMs in simple, pure C/CUDA with no need for 245MB of PyTorch or 107MB of cPython. Current focus is on pretraining, in particular reproducing the [GPT-2](https://github.com/openai/gpt-2) and [GPT-3](https://arxiv.org/abs/2005.14165) miniseries, along with a parallel PyTorch reference implementation
.vscode
<img src="img/banner.png" alt="LLM Course">
> A collection of papers and resources related to Large Language Models.
<p align="center">
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