Self-Rewarding Language Models

Language Model Self-Reward Training

CommonProductProductivityLanguage ModelSelf-Reward

This product is a self-rewarding language model trained using LLM as a judge and rewards signals generated by the model itself. Through iterative DPO training, the model not only improves its ability to follow instructions but also generates high-quality self-rewards. After three iterations of fine-tuning, this product has surpassed many existing systems, including Claude 2, Gemini Pro, and GPT-4 0613, on the AlpacaEval 2.0 leaderboard. While this work is preliminary research, it opens the door to the possibility of continuous improvement in the model in two key areas.

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Self-Rewarding Language Models — Language Model Self-Reward Training

Inception Labs — Inception Labs launches a new generation of diffusion-based large language models, offering extremely fast, efficient, and high-quality language generation capabilities.

OpenManus — OpenManus is an open-source intelligent agent project that can be used without an invitation code.

Instella — Instella is a high-performance open-source language model developed by AMD, designed to accelerate the development of open-source language models.

GPT-4.5 — OpenAI's latest language model, GPT-4.5, focuses on improving unsupervised learning capabilities and providing a more natural interactive experience.

Gemini 2.0 Flash-Lite — Gemini 2.0 Flash-Lite is a highly efficient language model optimized for long-text processing and diverse applications.

Phi-4-mini-instruct — Phi-4-mini-instruct is a lightweight, open-source language model focused on high-quality, inference-intensive data.

DeepSeek Japanese — DeepSeek is an advanced AI language model excelling in logical reasoning, mathematics, and programming tasks. It is available for free.

AlphaMaze-v0.2-1.5B — An innovative approach to enhance visual reasoning capabilities of large language models through solving text-based maze tasks.

AlphaMaze — AlphaMaze is a decoder language model focused on visual reasoning tasks, designed to address the limitations of traditional language models in visual tasks.

Smithery — Extends the capabilities of language models through Model Context Protocol servers.

Moonlight-16B-A3B — Moonlight-16B-A3B is a 16B parameter Mixture-of-Experts (MoE) model trained with the Muon optimizer for efficient language generation.

DeepHermes-3-Llama-3-8B-Preview — DeepHermes 3 is a large language model that supports both reasoning and regular response modes.

Lora — Lora is a local language model optimized for mobile devices, supporting iOS and Android platforms.

PaliGemma 2 mix — PaliGemma 2 mix is a versatile vision language model suitable for a variety of tasks and domains.

Mistral Saba — Mistral Saba is a regional language model specifically tailored for the Middle East and South Asia.

OLMoE app — Ai2 OLMoE is an open-source language model application that runs on iOS devices.

Xwen-Chat — Xwen-Chat is a collection of large language models focused on Chinese dialogue, offering multiple model versions and language generation services.

Exa & Deepseek Chat App — An open-source chat application that utilizes Exa's API for web searching and incorporates Deepseek R1 for inference.

DeepSeek-R1-Distill-Llama-8B — DeepSeek-R1-Distill-Llama-8B is a high-performance open-source language model suitable for text generation and inference tasks.

QwQ-32B-Preview-gptqmodel-4bit-vortex-v3 — This is a 4-bit quantized version based on the Qwen2.5-32B model, designed for efficient inference and low-resource deployment.

ReaderLM v2 — ReaderLM v2 is a cutting-edge small language model designed for HTML to Markdown and JSON conversion.

MiniMax-01 — A powerful language model with a total of 456 billion parameters, capable of processing context lengths of up to 4 million tokens.

MiniCPM-o-2_6 — MiniCPM-o 2.6 is a powerful multimodal large language model designed for visual, speech, and multimodal live applications.

MiniCPM-o — MiniCPM-o 2.6: An MLLM capable of delivering visual, voice, and multimodal interactions at GPT-4o level on mobile devices.

Llama-3-Patronus-Lynx-70B-Instruct — An open-source evaluation model for detecting hallucinations, based on the Llama-3 architecture with 70 billion parameters.

CAG — An enhancement method for language models that improves generation efficiency through preloading knowledge caches without the need for real-time retrieval.

Eurus-2-7B-PRIME — A 7B parameter language model trained based on the PRIME methodology, specifically designed to enhance reasoning capabilities.

Eurus-2-7B-SFT — Eurus-2-7B-SFT is a large language model optimized for mathematical capabilities, focusing on reasoning and problem-solving.

Sonus AI — Unlocker of future large language models