MykhaiIo's Stars
Mooler0410/LLMsPracticalGuide
A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)
brexhq/prompt-engineering
Tips and tricks for working with Large Language Models like OpenAI's GPT-4.
GoogleCloudPlatform/training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
GoogleCloudPlatform/generative-ai
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
gkamradt/langchain-tutorials
Overview and tutorial of the LangChain Library
langchain-ai/langgraph
Build resilient language agents as graphs.
tensorchord/Awesome-LLMOps
An awesome & curated list of best LLMOps tools for developers
tirthajyoti/Machine-Learning-with-Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
opendilab/DI-engine
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
IntelLabs/coach
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
pytorch/rl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
ndrplz/ConvLSTM_pytorch
Implementation of Convolutional LSTM in PyTorch.
oxwhirl/pymarl
Python Multi-Agent Reinforcement Learning framework
starry-sky6688/MARL-Algorithms
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
langchain-ai/langsmith-cookbook
abilzerian/LLM-Prompt-Library
Advanced Code and Text Manipulation Prompts for Various LLMs. Suitable for Siri, GPT-4o, Claude, Llama3, Gemini, and other high-performance open-source LLMs.
mohammadasghari/dqn-multi-agent-rl
Deep Q-learning (DQN) for Multi-agent Reinforcement Learning (RL)
guillaume-chevalier/Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP
What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
young-geng/CQL
Conservative Q Learning on top of SAC
isp1tze/MAProj
Multi-agent project (commnet, bicnet, maddpg) in pytorch for Multi-Agent Particle Environment
wjh720/QPLEX
WestlakeIntelligentRobotics/LLM-RL-Papers
Monitoring recent cross-research on LLM & RL on arXiv for control. If there are good papers, PRs are welcome.
johannah/bootstrap_dqn
Implementation of Bootstrap DQN and Randomized Prior Functions on ALE
zxsRambo/metalight
MetaLight: a value-based meta-reinforcement learning framework for traffic signal control
0b01/CommNet
PyTorch implementation of CommNet
gjp1203/nui_in_madrl
Negative Update Intervals in Multi-Agent Deep Reinforcement Learning
mjanschek/pytorch_seed_rl
A PyTorch implementation of SEED, originally created by Google Research for TensorFlow 2.
JoungheeKim/bootsrapped-dqn
This is pytorch implmentation project of Bootsrapped DQN
Amsterdam-Internships/Self-Learning-Traffic-Lights
Master thesis Artificial Intelligence at the University of Amsterdam as intern at the municipality of Amsterdam.
Jamesellis51015/CommNet-Reproduced-for-Levers-Task
A pytorch implementation of commNet on the levers task from "Learning Multiagent Communication with Backpropagation" paper. Reproduced from https://github.com/facebookarchive/CommNet