LlamaIndex 将 OCRia-1 推理速度提升近 10 倍并开源优化方案
There is so much alpha in this blog post for anyone learning model optimization. Check it out! http...
LlamaIndex 把把模型提速 10 倍的过程全写出来了：17 个小优化怎么测、怎么叠，还想给 vLLM 提 PR，做推理的可以看看。
LlamaIndex 基础设施团队发布博客，讲解如何让文档解析模型 OCRia-1 在单张 B200 GPU 上实现接近 10 倍的 token 生成提速。团队针对文档解析场景调优推理流程，每项改动都同时验证速度与精度，其中单项提升多为 2-5%，累计 17 项小优化叠加后效果显著。部分优化将回馈给开源的 vLLM 项目。
There is so much alpha in this blog post for anyone learning model optimization. Check it out! http...
There is so much alpha in this blog post for anyone learning model optimization. Check it out! llamaindex.ai/blog/the-infer… LlamaIndex 🦙 @llama_index We got OCRia-1 generating tokens nearly 10× faster on a single B200. Getting there meant making much better use of the same GPU. We tuned how OCRia-1 runs for the demands of document parsing, testing every change for both speed and accuracy. Some improvements were only 2–5%. Seventeen smaller optimizations later, “just a few percent” starts adding up. Our infrastructure team wrote up what worked, how they tested the changes, and what they learned about making document models run faster. We also plan to contribute some of these optimizations back to the open-source vLLM project. Read the full breakdown → llamaindex.ai/blog/the-infer… Watch the video below to see OCRia-1’s token generation before and after the optimizations. Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 2 🔄 2 ❤️ 9 👀 1144 📊 5 ⚡
- LlamaIndex11-03 16:49原文
