近日，一款名为StreamingLLM的开源方案在人工智能领域引起广泛关注。该方案在不到3个月的时间内，在GitHub上获得了5.7千颗星标，其最大的亮点在于可以在不牺牲生成效果和推理速度的前提下，实现多轮对话共400万个token的处理，将推理速度提升了22.2倍。
StreamingLLM是基于MIT成果的升级，其使用原生PyTorch实现，对于多轮对话推理场景的落地应用，具有低成本、低延迟、高吞吐等优势。然而，其在性能优化方面仍有空间。为此，Colossal-AI团队推出了SwiftInfer，这是一个基于TensorRT的StreamingLLM，可以进一步提升大模型推理性能46%，有效解决了上述问题。
SwiftInfer的推出，无疑为人工智能领域带来了新的突破，特别是在自然语言处理和多轮对话系统方面。未来，随着SwiftInfer的进一步优化和应用，我们有理由相信，人工智能的推理速度和效果将得到更大的提升。
英文翻译：
Recently, an open-source solution called StreamingLLM has garnered widespread attention in the field of artificial intelligence. In less than 3 months, it has received 5.7 thousand stars on GitHub. The most significant feature of this solution is its ability to handle multi-turn dialogue of up to 4 million tokens without sacrificing generation quality or inference speed, achieving a 22.2x speedup in inference.
StreamingLLM is an upgrade based on MIT成果, implemented using native PyTorch. For the deployment of multi-turn dialogue inference scenarios, it offers cost-effective, low-latency, and high-throughput advantages. However, there is still room for performance optimization. In response to this, the Colossal-AI team has launched SwiftInfer, a StreamingLLM-based solution on TensorRT that further enhances the inference performance of large models by 46%, effectively addressing the aforementioned issues.
The introduction of SwiftInfer无疑为人工智能领域带来了 a new breakthrough, especially in natural language processing and multi-turn dialogue systems. In the future, with further optimization and application of SwiftInfer, we have reason to believe that the inference speed and effectiveness of artificial intelligence will be greatly improved.
【来源】https://mp.weixin.qq.com/s/fiYSESKcOgZIDe8dpLdAdQ
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