human-feedback

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

A curated list of reinforcement learning with human feedback resources (continually updated)

Open-source pre-training implementation of Google's LaMDA in PyTorch. Adding RLHF similar to ChatGPT.

Let's build better datasets, together!

[CVPR 2024] Code for the paper "Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model"

BeaverTails is a collection of datasets designed to facilitate research on safety alignment in large language models (LLMs).

The ParroT framework to enhance and regulate the Translation Abilities during Chat based on open-sourced LLMs (e.g., LLaMA-7b, Bloomz-7b1-mt) and human written translation and evaluation data.

Implementation of Reinforcement Learning from Human Feedback (RLHF)

Product analytics for AI Assistants

The Prism Alignment Project

[ECCV2024] Towards Reliable Advertising Image Generation Using Human Feedback

Auditable human-feedback annotation, review, provenance, and frozen training-data export.

Dataset Viber is your chill repo for data collection, annotation and vibe checks.

Code for the paper "Aligning LLM Agents by Learning Latent Preference from User Edits".

[ICML 2024] Code for the paper "Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases"

Pause your AI agent. Ask a human. Resume with their answer. Open source human-in-the-loop (HITL) library for production LLM agents: Slack, email, and web dashboard. Typed Pydantic and Zod responses. Durable Temporal and LangGraph adapters. AI verifier. Audit trail. Self-hosted, Apache 2.0. Python and TypeScript.

[ NeurIPS 2023 ] Official Codebase for "Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback"

Documentation at

A selective persona agent for group chats and DMs with scoped memory, gated learning, context-aware participation, and the ability to stay silent when no response is needed.

Reinforcement Learning from Human Feedback with 🤗 TRL