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19:T9b0,<p><a href="https://dashscope.aliyun.com">API</a>
<a href="https://huggingface.co/spaces/Qwen/Qwen-Max-0428">DEMO</a>
<a href="https://discord.gg/yPEP2vHTu4">DISCORD</a></p>
<p>Previously, we opensourced a series of Qwen1.5 model ranging from 0.5 to 110 billion parameters. Now, we release a larger model, Qwen-Max-0428. Qwen-Max-0428 is an instruction-tuned model for chat service. Very recently, it is available via <a href="https://chat.lmsys.org/">Chatbot Arena</a> and it has now become the top-10 in the leaderboard. Furthermore, our evaluation of MT-Bench also demonstrates that the new model outperforms our previous largest model Qwen1.5-110B-Chat.</p>
<figure><img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/arena_leaderboard.jpg#center" alt="" loading="lazy"></figure>
<table>
    <tbody><tr>
        <th rowspan="1">Models</th>
        <th colspan="1">MT-Bench</th>
        <th colspan="1">Arena</th>
    </tr>
    <tr>
        <td>Qwen1.5-110B-Chat</td>
        <td>8.88</td>
        <td>1172</td>
    </tr>
    <tr>
        <td>Qwen-Max-0428</td>
        <td>8.96</td>
        <td>1186</td>
    </tr>
</tbody></table>
<p>We provide a demo of chat service of Qwen-Max-0428 (<a href="https://huggingface.co/spaces/Qwen/Qwen-Max-0428">link</a>) in Hugging Face Spaces:</p>
<iframe src="https://qwen-qwen-max-0428.hf.space" frameborder="0" width="850" height="1000"></iframe>
<p>It is also accessible through the official DashScope API (<a href="https://dashscope.aliyun.com">link</a>). Additionally, now the DashScope API is compatible with the OpenAI API format. Below is an example of usage:</p>
<pre><code class="language-python">from openai import OpenAI

client = OpenAI(
    api_key="$your-dashscope-api-key",
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
)

completion = client.chat.completions.create(
    model="qwen-max",
    messages=[{'role': 'system', 'content': 'You are a helpful assistant.'},
              {'role': 'user', 'content': 'Tell me something about large language models.'}]
)
print(completion.choices[0].message)
</code></pre>
<p>This model is available in our web service and APP (<a href="https://tongyi.aliyun.com/qianwen/">link</a>, only accessible in mainland China). Enjoy!</p>
<h1 id="citation">Citation</h1>
<pre><code>@misc{qwen1.5,
    title = {Introducing Qwen1.5},
    url = {https://qwenlm.github.io/blog/qwen1.5/},
    author = {Qwen Team},
    month = {February},
    year = {2024}
}
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