Practical_RL
awesome-RLHF
Our great sponsors
| Practical_RL | awesome-RLHF | |
|---|---|---|
| 2 | 6 | |
| 5,716 | 2,739 | |
| 1.2% | 8.3% | |
| 6.0 | 7.0 | |
| 17 days ago | 11 days ago | |
| Jupyter Notebook | ||
| The Unlicense | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Practical_RL
- [D] implementation of MCTS in Python
-
Alternatives to OpenAI’s spinning up?
there is this great github repo where there are lectures and other resources, and have a week by week jupyter notebooks where they explain and code with homeworks at the very end of it. is basics and deepRL, but just dqn and DDPG/ppo but i think will give you good start in the topic for later star working on your own.
awesome-RLHF
-
OpenDILab Awesome Paper Collection: RL with Human Feedback （3）
Recently, OpenDILab made a paper collection about Reinforcement Learning with Human Feedback (RLHF) and it has been open-sourced on GitHub. This repository is dedicated to helping researchers to collect the latest papers on RLHF, so that they can get to know this area better and more easily.
-
Awesome RLHF (RL with Human Feedback) This is a collection of research papers for Reinforcement Learning with Human Feedback (RLHF). And the repository will be continuously updated to track the frontier of RLHF. Welcome to follow and star! https://github.com/opendilab/awesome-RLHF
Welcome to follow and star! https://github.com/opendilab/awesome-RLHF
-
OpenDILab Awesome Paper Collection: RL with Human Feedback （1）
Here we’re gonna introduce a new repository open-sourced by OpenDILab. Recently, OpenDILab made a paper collection about Reinforcement Learning with Human Feedback (RLHF) and it has been open-sourced on GitHub. This repository is dedicated to helping researchers to collect the latest papers on RLHF, so that they can get to know this area better and more easily. About RLHF Reinforcement Learning with Human Feedback (RLHF) is an extended branch of Reinforcement Learning (RL) that allows the RLHF family of methods to incorporate human feedback into the training process by using this feedback to construct By using this feedback to build a reward model neural network that provides reward signals to help RL intelligences learn, human needs, preferences, and perceptions can be more naturally communicated to the intelligence in an interactive learning manner, aligning the optimization goals between humans and artificial intelligence to produce systems that behave in a manner consistent with human values. Reinforcement Learning with Human Feedback (RLHF) is an extended branch of Reinforcement Learning. When the optimization goal is abstract and it's very difficult to define the specific reward function, RLHF can help to put human feedback into the training process. This feedback can be constructed into a reward neural network model so that RL agents can learn from the given reward signal and naturally convey human needs, preference and attitude to agents through interactive learning.
- A collection of research papers for Reinforcement Learning with Human Feedback (RLHF)
What are some alternatives?
webdataset - A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
LaMDA-rlhf-pytorch - Open-source pre-training implementation of Google's LaMDA in PyTorch. Adding RLHF similar to ChatGPT.
FunMatch-Distillation - TF2 implementation of knowledge distillation using the "function matching" hypothesis from https://arxiv.org/abs/2106.05237.
deep-learning-drizzle - Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
awesome-rl - Reinforcement learning resources curated
hh-rlhf - Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
visual-chatgpt - Official repo for the paper: Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models [Moved to: https://github.com/microsoft/TaskMatrix]
alpha-zero-general - A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
redisai-examples - RedisAI showcase
TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos
YPDL-Build-a-movie-recommendation-engine-with-TensorFlow - In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.