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Thoraipakkam, Chennai - 600097. The Department of CSE, in collaboration with AIDS, CSBS, and IT, is organizing a one-day workshop on "Deep Learning" on 28/03/2025. Upcoming …

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MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models and has industry-leading performance for inference and training on-device.

2025年2月1日 · 本文将从框架概述、性能对比、内存消耗、硬件支持等多个角度对 TNN、MNN 和 NCNN 进行详细对比，并介绍相关的推理公式和逻辑图。 TNN 是腾讯开发的高效深度学习推理框架，专为移动端和 嵌入式设备 优化。 特点： 高性能：通过内存优化和多线程加速，适合多平台部署。 多平台支持：支持 ARM、X86、NPU 等多种硬件平台。 灵活性：支持多种深度学习框架和模型格式，如 Caffe、TensorFlow。 MNN 是阿里巴巴开发的开源深度学习推理框架，专注于移 …

基于MNN开发的LLM推理引擎，支持目前主流的开源LLM模型。 该功能分为2部分： llmexport 是一个llm模型导出工具，能够将llm模型导出为onnx和mnn模型。 clone 后检查一下模型大小，有可能因为lfs没安装导致下载的是空模型. # 导出模型，tokenizer和embedding，并导出对应的mnn模型 . --path /path/to/Qwen2-0.5B-Instruct \ --export mnn. ├── config.json. ├── embeddings_bf16.bin. ├── llm.mnn.json. ├── llm.mnn.weight. ├── onnx/ ├──llm.onnx.data. ├── llm_config.json.

MNN-LLM: A Generic Inference Engine for Fast Large Language Model Deployment on Mobile Devices. 论文地址： https:// dl.acm.org/doi/pdf/10.1 145/3700410.3702126. 源码地址： https:// github.com/alibaba/MNN. 运行文档： 大语言模型 - MNN-Doc 2.1.1 documentation. 文章发表在MMAsia'24: ACM Multimedia Asia Workshops会议 ...