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[version] release v0.9.5 (#10532)
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README_zh.md
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README_zh.md
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[](https://colab.research.google.com/drive/1d5KQtbemerlSDSxZIfAaWXhKr30QypiK?usp=sharing)
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[](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory)
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[](https://www.lab4ai.cn/course/detail?id=7c13e60f6137474eb40f6fd3983c0f46&utm_source=LLaMA-Factory)
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[](https://www.llamafactory.com.cn/?utm_source=LLaMA-Factory)
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[](https://huggingface.co/spaces/hiyouga/LLaMA-Board)
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[](https://modelscope.cn/studios/hiyouga/LLaMA-Board)
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[](https://novita.ai/templates-library/105981?sharer=88115474-394e-4bda-968e-b88e123d0c47)
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</div>
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👋 加入我们的[微信群](https://github.com/hiyouga/llamafactory-community/blob/main/wechat/main.jpg)、[NPU 用户群](https://github.com/hiyouga/llamafactory-community/blob/main/wechat/npu.jpg)、[大模型实验室群](https://github.com/hiyouga/llamafactory-community/blob/main/wechat/lab4ai.jpg) 或 [LLaMA Factory Online 用户群](https://github.com/hiyouga/llamafactory-community/blob/main/wechat/online.png)。
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👋 加入我们的[微信群](https://github.com/hiyouga/llamafactory-community/blob/main/wechat/main.jpg)和 [NPU 用户群](https://github.com/hiyouga/llamafactory-community/blob/main/wechat/npu.jpg)。
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\[ [English](README.md) | 中文 \]
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开始云端训练:
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- **Colab(免费)**:https://colab.research.google.com/drive/1d5KQtbemerlSDSxZIfAaWXhKr30QypiK?usp=sharing
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- **PAI-DSW(免费试用)**:https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory
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- **LLaMA Factory Online(在线微调)**:https://www.llamafactory.com.cn/?utm_source=LLaMA-Factory
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- **九章智算云(算力优惠活动)**:https://docs.alayanew.com/docs/documents/useGuide/LLaMAFactory/mutiple/?utm_source=LLaMA-Factory
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阅读技术文档:
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- **入门教程**:https://zhuanlan.zhihu.com/p/695287607
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- **框架文档**:https://llamafactory.readthedocs.io/zh-cn/latest/
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- **框架文档(昇腾 NPU)**:https://ascend.github.io/docs/sources/llamafactory/
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- **官方博客**:https://blog.llamafactory.net/
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- **官方课程**:https://www.lab4ai.cn/course/detail?id=7c13e60f6137474eb40f6fd3983c0f46&utm_source=LLaMA-Factory
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> [!NOTE]
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> 除上述链接以外的其他网站均为未经许可的第三方网站,请小心甄别。
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- [数据准备](#数据准备)
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- [快速开始](#快速开始)
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- [LLaMA Board 可视化微调](#llama-board-可视化微调由-gradio-驱动)
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- [LLaMA Factory Online 在线微调](#llama-factory-online-在线微调)
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- [构建 Docker](#构建-docker)
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- [利用 vLLM 部署 OpenAI API](#利用-vllm-部署-openai-api)
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- [从魔搭社区下载](#从魔搭社区下载)
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- 💡 [KTransformers Fine-Tuning × LLaMA Factory: 用2张4090级的GPU+CPU 微调 1000B规模的超大模型](https://swcil84qspu.feishu.cn/wiki/Z1sSwb2poijybxkyPEkcDG6enVc) (中文)
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- 💡 [Easy Dataset × LLaMA Factory: 让大模型高效学习领域知识](https://buaa-act.feishu.cn/wiki/KY9xwTGs1iqHrRkjXBwcZP9WnL9)(中文)
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- [使用 LLaMA-Factory 微调心理健康大模型](https://www.lab4ai.cn/project/detail?id=25cce32ec131497b9e06a93336a0817f&type=project&utm_source=LLaMA-Factory)(中文)
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- [使用 LLaMA-Factory 构建 GPT-OSS 角色扮演模型](https://docs.llamafactory.com.cn/docs/documents/best-practice/gptroleplay/?utm_source=LLaMA-Factory)(中文)
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- [基于 LLaMA-Factory 和 EasyR1 打造一站式无代码大模型强化学习和部署平台 LLM Model Hub](https://aws.amazon.com/cn/blogs/china/building-llm-model-hub-based-on-llamafactory-and-easyr1/)(中文)
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- [通过亚马逊 SageMaker HyperPod 上的 LLaMA-Factory 增强多模态模型银行文档的视觉信息提取](https://aws.amazon.com/cn/blogs/machine-learning/how-apoidea-group-enhances-visual-information-extraction-from-banking-documents-with-multimodal-models-using-llama-factory-on-amazon-sagemaker-hyperpod/)(英文)
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<details><summary>全部博客</summary>
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- [使用 LLaMA-Factory 微调 Llama3.1-70B 医学诊断模型](https://docs.alayanew.com/docs/documents/bestPractice/bigModel/llama70B/?utm_source=LLaMA-Factory)(中文)
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- [使用 LLaMA-Factory 微调 Qwen2.5-VL 实现自动驾驶场景微调](https://docs.alayanew.com/docs/documents/useGuide/LLaMAFactory/mutiple/?utm_source=LLaMA-Factory)(中文)
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- [LLaMA Factory:微调 DeepSeek-R1-Distill-Qwen-7B 模型实现新闻标题分类器](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)(中文)
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- [基于 Amazon SageMaker 和 LLaMA-Factory 打造一站式无代码模型微调部署平台 Model Hub](https://aws.amazon.com/cn/blogs/china/a-one-stop-code-free-model-fine-tuning-deployment-platform-based-on-sagemaker-and-llama-factory/)(中文)
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- [LLaMA Factory 多模态微调实践:微调 Qwen2-VL 构建文旅大模型](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl)(中文)
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llamafactory-cli webui
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```
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### LLaMA Factory Online 在线微调
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详情阅读该[文档](https://docs.llamafactory.com.cn/docs/documents/quickstart/getstarted/?utm_source=LLaMA-Factory)。
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### 构建 Docker
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CUDA 用户:
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