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openchat (OpenChat)
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Advancing Open-source Language Models with Mixed-Quality Data

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\n \n \"OpenChat\n Online Demo\n |\n \n \"GitHub\n GitHub\n |\n \n \"ArXiv\n Paper\n |\n \n \"Discord\n Discord\n \n

\n\n OpenChat is dedicated to advancing and releasing **open-source language models**, fine-tuned with our [**C-RLFT**](https://arxiv.org/pdf/2309.11235.pdf) technique, which is inspired by offline reinforcement learning. Our models learn from mixed-quality data without preference labels, delivering exceptional performance on par with `ChatGPT`, which we were the first to beat with only `7B` parameter LLMs which can be run on a **consumer GPU (e.g. RTX 3090)**.\n\n# 💌Contact\n\n**Project Lead:**\n- Guan Wang [imonenext@gmail.com]\n- [Alpay Ariyak](https://github.com/alpayariyak) [alpay@ariyak.ai]\n\n**Sponsors:**\n- [Sen Song](https://scholar.google.com/citations?user=cYgtRP4AAAAJ) (Tsinghua University)\n- [Yang Liu](https://nlp.csai.tsinghua.edu.cn/~ly/) (Tsinghua University)\n- [01.AI Company](https://www.lingyiwanwu.com/en)\n- [RunPod](https://www.runpod.io/)","html":"
\n \n \n \n

Advancing Open-source Language Models with Mixed-Quality Data

\n
\n\n

\n \n \"OpenChat\n Online Demo\n |\n \n \"GitHub\n GitHub\n |\n \n \"ArXiv\n Paper\n |\n \n \"Discord\n Discord\n \n

\n\n

OpenChat is dedicated to advancing and releasing open-source language models, fine-tuned with our C-RLFT technique, which is inspired by offline reinforcement learning. Our models learn from mixed-quality data without preference labels, delivering exceptional performance on par with ChatGPT, which we were the first to beat with only 7B parameter LLMs which can be run on a consumer GPU (e.g. RTX 3090).

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💌Contact

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Project Lead:

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Sponsors:

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Advancing Open-source Language Models with Mixed-Quality Data

OpenChat Logo Online Demo | GitHub Logo GitHub | ArXiv Logo Paper | Discord Logo Discord

OpenChat is dedicated to advancing and releasing open-source language models, fine-tuned with our C-RLFT technique, which is inspired by offline reinforcement learning. Our models learn from mixed-quality data without preference labels, delivering exceptional performance on par with ChatGPT, which we were the first to beat with only 7B parameter LLMs which can be run on a consumer GPU (e.g. RTX 3090).

💌Contact

Project Lead:

Sponsors: