OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

Unified Efficient Fine-Tuning of 100+ LLMs (ACL 2024)

The official GitHub page for the survey paper "A Survey of Large Language Models".

中文LLaMA-2 & Alpaca-2大模型二期项目 + 64K超长上下文模型 (Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models)

Official release of InternLM2.5 base and chat models. 1M context support

Robust recipes to align language models with human and AI preferences

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

Fine-tuning ChatGLM-6B with PEFT | 基于 PEFT 的高效 ChatGLM 微调

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

A Doctor for your data

Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.

WebGLM: An Efficient Web-enhanced Question Answering System (KDD 2023)

An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.

Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback

[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences for Text-to-image Generation

Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.

Recipes to train reward model for RLHF.

A library with extensible implementations of DPO, KTO, PPO, ORPO, and other human-aware loss functions (HALOs).

[NeurIPS 2024] SimPO: Simple Preference Optimization with a Reference-Free Reward

Aligning Large Language Models with Human: A Survey