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本文作者提出了LORA低资源训练方法，让普通玩家有了微调大模型的可能。 更重要的是作者用大量实验和理论分析为我们讲解LORA微调背后的原理，让我们能够更加容易掌握和理解LORA微调过程。 LoRa技术是基于Semtech公司的低功耗广域网无线标准，采用chirp spread spectrum扩频调制，实现长距离、低功耗通信，适用于智能城市、农业监测等领域。 本文深入剖析了LoRA模型，它是用于微调大型语言模型的低秩适应技术，在Stable Diffusion模型应用中很受欢迎。 介绍了其工作原理、查找和使用方法，还给出使用注意事项，并列举了一些LoRA模型示例，具有高效、灵活等优点。
示例的训练记录公开链接如下，供参考 图表 ｜ Qwen3-Lora/Qwen3-8B-LoRA-shufan.jiang 加载 lora 权重推理 得到任意 checkpoints 之后加载 lora 权重进行推理： from transformers import AutoModelForCausalLM, AutoTokenizer import torch from peft import PeftModel mode_path = '请修改我！ ！！ /Qwen/Qwen3-8B. LoRa，全称Long Range Radio，即远距离 无线通信。 它是一种低功耗广域网（LPWAN）协议，具有传输距离长，功耗低和成本低的特点。 文章介绍了LoRA及其多种变体，如LoRA+、VeRA、LoRA-FA等，每种变体都通过独特的方法改进了LoRA的性能和资源消耗，展示了其在自然语言处理任务中的应用潜力。
LoRa （Lo ng Ra nge）是Semtech開發的 LPWAN 協定，是依 chirp展頻 （CSS）技術衍生的展頻調變技術為基礎 [1]。 是由法國 格勒諾布爾 的Cycleo公司所發展，後來被LoRa Alliance的創立成員 Semtech 所收購 [2]。
什么是LoRA模型，如何使用和训练LoRA模型？ 你想要的都在这！ 总的来说，LoRa是一种物理层技术，提供了长距离、低功耗、低速率的无线通信，而LoRaWAN则是基于LoRa技术开发的一种通信协议，主要应用于物联网中的低功耗广域网络。 新一代無線傳輸技術LoRa 隨著智慧城市應用發展成熟，LoRa技術中，智能感測無論在醫療、商業、建築、交通等領域上可以透過數據AI分析，進而形成相關應用，並能蒐集巨量數據。
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