willdphan

ragapp

The easiest way to use Agentic RAG in any enterprise

Dot

Text-To-Speech, RAG, and LLMs. All local!

distilabel

⚗️ distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency.

bonito

A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.

DataDreamer

DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models.   🤖💤

textbook_quality

Generate textbook-quality synthetic LLM pretraining data

llm-data-creation

Model, Code & Data for the EMNLP'23 paper "Making Large Language Models Better Data Creators"

awesome-deep-learning-papers

The most cited deep learning papers

Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

torchtitan

A native PyTorch Library for large model training

dspy

DSPy: The framework for programming—not prompting—foundation models

dora

Dataflow-Oriented Robotic Application is middleware that streamlines and simplifies the creation of AI-based robotic applications with low latency, composable, and distributed dataflow.

minimalRL

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

llm.c

LLM training in simple, raw C/CUDA

pytorch-rl

Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

Simple-MuJoCo-PickNPlace

Very simple MuJoCo Pick and Place task using Panda

mujoco_menagerie

A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.

MuJoCo_RL_UR5

A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.

Gymnasium

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

Robot-Learning-UT

Simulation of a neural network model using Deep Deterministic Policy Gradient (DDPG) improved with Hindsight Experience Replay (HER) in the Fetch Reach and Pick and Place environments of Gym Open AI.

hindsight-experience-replay

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

rl-baselines3-zoo

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

cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

CORL

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

Hands-On-Reinforcement-Learning-With-Python

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

MuJoCo-Tutorial

Tutorial on how to get started with MuJoCo Simulation Platform. MuJoCo stands for Multi-Joint dynamics with Contact. It was acquired and made freely available by DeepMind in October 2021, and open sourced in May 2022. Feel free to contribute. Show your support by ✨this repository.

tokencost

Easy token price estimates for LLMs

act