nanochat is the simplest experimental harness for training LLMs. It is designed to run on a single GPU node, the code is minimal/hackable, and it covers all major LLM stages including tokenization, pretraining, finetuning, evaluation, and inference.
Global
#2748 · +8 · 1d ·GitHub
由吴恩达老师与 OpenAI 合作推出的大模型系列教程，从大模型时代开发者的基础技能出发，深入浅出地介绍了如何基于大模型 API、LangChain 架构快速开发结合大模型强大能力的应用。其中，《Prompt Engineering for Developers》教程面向入门 LLM 的开发者，深入浅出地介绍了对于开发者，如何构造 Prompt 并基于 OpenAI 提供的 API 实现包括总结、推断、转换等多种常用功能，是入门 LLM 开发的经典教程；《Building Systems with the ChatGPT API》教程面向想要基于…
CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features. The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch.
verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
#4489 · +3 · 1d ·GitHub
A docker image containing the code and the dependencies is available on DockerHub. 03):
Ensure PyTorch and CUDA are installed. The repo needs CUDA extensions to be built. If not present, run the following commands: