awesome-RLHF VS LaMDA-rlhf-pytorch

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.

Welcome to follow and star! https://github.com/opendilab/awesome-RLHF

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.

I made a mistake about the LaMDa, what I mean is the machine learning model that Lamda based on: Transformer. Though you can still access to the paper: [2201.08239] LaMDA: Language Models for Dialog Applications (arxiv.org) and a pyTorch implementation here: conceptofmind/LaMDA-rlhf-pytorch: Open-source pre-training implementation of Google's LaMDA in PyTorch. Adding RLHF similar to ChatGPT. (github.com)

I know it'll be 10 times worse for now at best since this is refined proprietary tech where a lot of resources went into but I'm still looking forward to something aiming to achieve this level of fluency and context understanding that can be used open and freely. Closest thing I could find so far might be GPT2 or laMDA?

An open-source implementation for the pre-training architecture of Google's LaMDA in PyTorch. The research paper outlines an autoregressive, decoder-only, GPT-like transformer language model. The transformer uses T5 relative positional bias in the attention layers and gated-GELU activation function in the feed-forward layers.

The repository currently contains a script for basic training as well as Huggingface datasets and Weights & Biases integration.

LaMDA research paper: https://arxiv.org/abs/2201.08239

Github repository for the model: https://github.com/conceptofmind/LaMDA-pytorch

The pre-training architecture was peer-reviewed by Dr. Phil Wang. Please check out and support his work: https://github.com/lucidrains.

Updates: https://twitter.com/EnricoShippole

If you want to view the pre-training architecture of a transformer model such as LaMDA, the one you are referencing in this post, you can view that here: https://github.com/conceptofmind/LaMDA-pytorch/blob/main/lamda_pytorch/lamda_pytorch.py

An example for an iterable data loader like this would be: https://github.com/conceptofmind/LaMDA-pytorch/blob/main/dataloader/stream_dataloader.py

Github repository for the model: https://github.com/conceptofmind/LaMDA-pytorch