Live components for your LLM

Adaptive Non Deterministic Yoloing

A collection of useful environments for testing Reinforcement Learning algorithms. Designed (mostly) with discrete, graph-based methods in mind.

An elegant PyTorch deep reinforcement learning library.

A Python package that provides a simple framework for working with Options in Reinforcement Learning.

Spiral's Machine Learning Library

Machine learning library, Distributed training, Deep learning, Reinforcement learning, Models, tensorflow, pytorch

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

A collection of MARL benchmarks based on TorchRL

A space-themed OpenAI Gym environment designed for reinforcement learning. Users pilot a spaceship through an asteroid field while collecting coins. The environment increases in difficulty as the speed escalates, with asteroids and coins spawning randomly, providing dynamic challenges that are ideal for developing and refining Agents

⚡ Flashbax: Accelerated Replay Buffers in JAX

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Stateful implementations of OPE algorithms, designed for use in the development of offline RL models

PyTorch implementations for deep and classical rl algorithms

HPO and Architecture Benchmarking for RL: Dynamically, Reactive and Efficient

基于gym的pytorch深度强化学习(DRL)(PPO,PPG,DQN,SAC,DDPG,TD3等算法)

Originally from: https://github.com/kevinh42/gym2real_isaacgym

Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).

Video Diffusion Alignment via Reward Gradients. We improve a variety of video diffusion models such as VideoCrafter, OpenSora, ModelScope and StableVideoDiffusion by finetuning them using various reward models such as HPS, PickScore, VideoMAE, VJEPA, YOLO, Aesthetics etc.