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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).

I implemented a transformer model from scratch using PyTorch, based on the paper Attention is All You Need. You can use my scripts to train your own billion or million parameter LLM using a single GPU.

🐧 PenguinHarness: Local-first multi-agent app development platform - create, fine-tune, deploy AI apps automatically!

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

Code and documentation to train Stanford's Alpaca models, and generate the data.

Thank you for developing with Llama models. 1 release, we’ve consolidated GitHub repos and added some additional repos as we’ve expanded Llama’s functionality into being an e2e Llama Stack.

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

> A collection of papers and resources related to Large Language Models. > > The organization of papers refers to our survey "A Survey of Large Language Models". ) > > > If you find our survey useful for your research, please cite the following paper:

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

A curated (still actively updated) list of practical guide resources of LLMs. It's based on our survey paper: Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond and efforts from @xinyadu. The survey is partially based on the second half of this Blog.