Popular GitHub Repositories for Amazon Q

《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程

强化学习中文教程（蘑菇书?），在线阅读地址：https://datawhalechina.github.io/easy-rl/

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型）

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.

? wukong-robot 是一个简单、灵活、优雅的中文语音对话机器人/智能音箱项目，支持ChatGPT多轮对话能力，还可能是首个支持脑机交互的开源智能音箱项目。

Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Artificial Intelligence Infrastructure-as-Code Generator.

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

A library for training and deploying machine learning models on Amazon SageMaker

A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. ?25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. ? Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

A conversational Q&A agent configuration system, self-hosted deployment solutions, and a convenient all-in-one application SDK, allowing you to create intelligent Q&A bots for your GitHub repositories

✨ Add autocomplete and AI to your existing terminal on macOS & Linux

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS