近日，阿里巴巴的通义千问团队在人工智能领域取得了重大突破，正式发布了Qwen系列的首个大规模并行模型——Qwen1.5-MoE-A2.7B。这款模型以其卓越的性能和高效的资源利用率，引发了业界的广泛关注。
Qwen1.5-MoE-A2.7B拥有27亿个激活参数，尽管参数规模相对较小，但它在性能上与当前具有70亿参数的顶尖模型，如Mistral 7B和Qwen1.5-7B，展现出相当的竞争力。值得注意的是，Qwen1.5-MoE-A2.7B的Non-Embedding参数仅为20亿，仅为Qwen1.5-7B（包含65亿Non-Embedding参数）的三分之一，实现了模型规模的显著压缩。
在资源效率方面，Qwen1.5-MoE-A2.7B的训练成本降低了75%，这意味着在保持高性能的同时，大大降低了计算资源的需求。此外，该模型在推理速度上也实现了显著提升，速度比Qwen1.5-7B快了1.74倍，为实际应用提供了更快的响应时间和更高的运行效率。
这一创新成果的发布，不仅彰显了通义千问团队在模型优化和效率提升上的技术实力，也为大规模预训练模型的未来发展提供了新的方向。据消息来源，这一突破性进展来自于阿里魔搭社区，该社区在推动人工智能技术的创新和应用上一直扮演着重要角色。
英语如下：
**News Title:** “Alibaba Qwen千问 Introduces Qwen1.5-MoE-A2.7B: High-Performance Large Model with Half the Parameters and Double the Speed!”
**Keywords:** Qwen1.5-MoE-A2.7B, Performance Boost, Cost Reduction
**News Content:**
**Title:** Alibaba Qwen千问 Team Launches High-Performance MoE Model Qwen1.5-MoE-A2.7B
Recently, the Qwen千问 team at Alibaba made a significant breakthrough in the field of artificial intelligence with the official release of Qwen1.5-MoE-A2.7B, the first large-scale parallel model in the Qwen series. This model has drawn widespread attention due to its exceptional performance and efficient resource utilization.
Qwen1.5-MoE-A2.7B boasts 2.7 billion active parameters. Despite its relatively smaller size, it competes favorably with top models like Mistral 7B and Qwen1.5-7B, both of which have 7 billion parameters. Notably, Qwen1.5-MoE-A2.7B has only 2 billion Non-Embedding parameters, a third of Qwen1.5-7B’s 6.5 billion, resulting in a significant reduction in model size.
In terms of resource efficiency, the training cost of Qwen1.5-MoE-A2.7B has been reduced by 75%, allowing for high performance while minimizing the demand for computational resources. Moreover, the inference speed has been notably enhanced, achieving a 1.74 times faster speed than Qwen1.5-7B, providing faster response times and higher operational efficiency for practical applications.
This innovative achievement underscores the Qwen千问 team’s technical prowess in model optimization and efficiency enhancement, while also pointing to a new direction for the future development of large-scale pre-training models. Sources indicate that this breakthrough进展 stems from the Alibaba ModelScope community, which has consistently played a crucial role in driving innovation and application of AI technologies.
【来源】https://mp.weixin.qq.com/s/6jd0t9zH-OGHE9N7sut1rg
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