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

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

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

Official release of InternLM series (InternLM, InternLM2, InternLM2.5, InternLM3).

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)

Robust recipes to align language models with human and AI preferences

OpenClaw-RL: Train any agent simply by talking

The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.

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

Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.

Align Anything: Training All-modality Model with Feedback

Implement a reasoning LLM in PyTorch from scratch, step by step

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

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

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.

An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models

🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.

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

Textbook on reinforcement learning from human feedback