To contribute to this GitHub project, you can follow these steps:
1. Fork the repository you want to contribute to by clicking the "Fork" button on the project page.
Explore
61,593 skills indexed with the new KISS metadata standard.
1. Fork the repository you want to contribute to by clicking the "Fork" button on the project page.
*.dev.yaml
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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)
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.
<p align="left"><img src="https://github.com/potacho/power_bi_workshop/blob/master/images/logo.png"></p>
Due to projects like [Explore the LLMs](https://llm.extractum.io/) specializing in model indexing, the custom list has been removed.
text2image:
- [EnCodec](https://github.com/facebookresearch/encodec) SOTA deep learning based audio codec supporting both mono 24 kHz audio and stereo 48 kHz audio
- The model list moved [here](llm-model-list.md)