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README.md
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<h1 style="font-size: 2em;">OpenChat </h1>
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<h1 style="font-size: 1.50em;">Advancing Open-source Language Models with Mixed-Quality Data</h1>
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<p align="center" style="margin-top: 0px; font-size: 1.5em;">
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<a href="https://huggingface.co/openchat/openchat_3.5" style="text-decoration: none; color:
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<span style="color: #0056b3; font-weight: bold;">3.5</span>
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</a>
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<br>
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<strong>π₯ First <u>7B</u> model that Achieves Comparable Results with <u>ChatGPT</u> (March)!
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π₯</strong>
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<br>
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<strong>π <u>#1</u> Open-source model on MT-bench scoring 7.81, outperforming <u>70B</u> models π </strong>
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<div align="center" style="display: flex; justify-content: center; align-items: center;">
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<img src="https://github.com/imoneoi/openchat/raw/master/assets/openchat.png" style="width:
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<img src="https://github.com/imoneoi/openchat/raw/master/assets/openchat_grok.png" style="width:
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- OpenChat is an innovative library of **open-source language models**, fine-tuned with [**C-RLFT**](https://arxiv.org/pdf/2309.11235.pdf) - a strategy inspired by offline reinforcement learning.
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<link href='https://fonts.googleapis.com/css?family=Source+Sans+Pro' rel='stylesheet' type='text/css'>
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<p align="center" style="margin-top: 0px; font-size: 1.5em; background-color: #0056b3; padding: 0.5em; border-radius: 0.5em; color: white">
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<a href="https://huggingface.co/openchat/openchat_3.5" style="text-decoration: none; color: white">
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<span style="font-size: 1.8em; ">OpenChat 3.5</span>
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<br>
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<strong>π₯ First <u>7B</u> model that Achieves Comparable Results with <u>ChatGPT</u> (March)!
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π₯</strong>
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<br>
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<strong>π <u>#1</u> Open-source model on MT-bench scoring 7.81, outperforming <u>70B</u> models π </strong>
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</a>
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</p>
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<div align="center" style="display: flex; justify-content: center; align-items: center;">
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<img src="https://github.com/imoneoi/openchat/raw/master/assets/openchat.png" style="width:45%; margin-right: 2%;">
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<img src="https://github.com/imoneoi/openchat/raw/master/assets/openchat_grok.png" style="width: 47%;">
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</div>
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- OpenChat is an innovative library of **open-source language models**, fine-tuned with [**C-RLFT**](https://arxiv.org/pdf/2309.11235.pdf) - a strategy inspired by offline reinforcement learning.
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