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1. Fork the repository you want to contribute to by clicking the "Fork" button on the project page.
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
*.dev.yaml
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">
__pycache__/
These LLMs (Large Language Models) are all licensed for commercial use (e.g., Apache 2.0, MIT, OpenRAIL-M). Contributions welcome!
- [ModelScope Text to video synthesis](https://huggingface.co/spaces/damo-vilab/modelscope-text-to-video-synthesis)
<p align="left"><img src="https://github.com/potacho/power_bi_workshop/blob/master/images/logo.png"></p>
Collection of all things "Data Science" leaning towards Marketing & Advertisement (Digital Marketers, Agencies, Web Designers and Web Analysts)
- Want to know which one is "the best"? Have a look at the [🏆 Leaderboards](llm-tools.md#benchmarking) in the Benchmarking section.
Due to projects like [Explore the LLMs](https://llm.extractum.io/) specializing in model indexing, the custom list has been removed.
**Important:**
text2image:
- The model list moved [here](llm-model-list.md)