2025-09-02 13:05:04 +08:00
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Quickstart
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---
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### Docker Image
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2025-09-18 16:48:02 +08:00
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自行联系沐曦官方获取下载链接
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2025-09-02 13:05:04 +08:00
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```bash
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2025-09-18 16:48:02 +08:00
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docker pull cr.metax-tech.com/public-ai-release/maca/diffusers.training:maca.ai3.0.0.5-torch2.4-py310-ubuntu22.04-amd64
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```
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### 模型
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stable-diffusion-v1-5, 下载地址:
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- [modelscope](https://modelscope.cn/models/AI-ModelScope/stable-diffusion-v1-5)
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- [hugging face](https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5)
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### 测试程序
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1. 准备输入数据集，可以参考示例`dataset.json`
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2. 在docker镜像里运行测试程序，会根据`dataset.json`内容，在`output`目录下生成图片文件。
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3. 示例使用 [metax-docker](https://developer.metax-tech.com/softnova/category?package_kind=Cloud&dimension=metax&chip_name=%E6%9B%A6%E4%BA%91C500%E7%B3%BB%E5%88%97&deliver_type=%E5%88%86%E5%B1%82%E5%8C%85&series_name=metax-docker) 做为演示 docker runtime, 如用原生 docker 需自行挂载 GPU 等设备到容器
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### 完整示例
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```bash
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git clone https://git.modelhub.org.cn:9443/EngineX-MetaX/enginex-c_series-diffusers
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docker pull cr.metax-tech.com/public-ai-release/maca/diffusers.training:maca.ai3.0.0.5-torch2.4-py310-ubuntu22.04-amd64
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cd enginex-c_series-diffusers/
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# git clone 先确认 git-lfs 已安装
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git lfs install
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git clone https://www.modelscope.cn/AI-ModelScope/stable-diffusion-v1-5.git
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2025-09-18 16:48:02 +08:00
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metax-docker run --gpus=[0] -it --entrypoint /bin/bash -v $(realpath .):/workspace/app -v $(realpath stable-diffusion-v1-5):/model --entrypoint /bin/bash cr.metax-tech.com/public-ai-release/maca/diffusers.training:maca.ai3.0.0.5-torch2.4-py310-ubuntu22.04-amd64
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2025-09-02 13:05:04 +08:00
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#> inside container
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cd app/
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python3 main.py \
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--model "/model" \
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--json "dataset.json" \
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--results "results.json" \
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--outdir "output" \
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--device cuda \
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--dtype fp16
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```
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### 测试结果
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| | A100 平均生成时间（秒） | MetaX C500 平均生成时间（秒） |
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|------|-------------------------|----------------------------|
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| 时间 | 2.2142 | 4.5260 |
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