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Linux command

sd-cli 命令

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复制后可按需替换文件名、目录或参数。

常用示例

Generate an image from a text prompt

sd-cli -m [model.safetensors] -p "[a photo of a cat]" -o [output.png]

Generate with specific dimensions

sd-cli -m [model.safetensors] -p "[prompt]" --width [512] --height [512] -o [output.png]

Set generation parameters

sd-cli -m [model.safetensors] -p "[prompt]" --steps [20] --cfg-scale [7.0] --seed [42] -o [output.png]

Use a specific sampling method

sd-cli -m [model.safetensors] -p "[prompt]" --sampling-method [euler_a] -o [output.png]

Generate with negative prompt

sd-cli -m [model.safetensors] -p "[prompt]" -n "[blurry, low quality]" -o [output.png]

Image-to-image generation

sd-cli -m [model.safetensors] --img2img [input.png] -p "[oil painting style]" --strength [0.75] -o [output.png]

说明

sd-cli is the command-line interface for stable-diffusion.cpp, a lightweight C/C++ implementation of Stable Diffusion using the ggml tensor library. It runs image generation models on CPU and GPU without requiring Python or heavy ML frameworks. The tool supports Stable Diffusion 1.x, 2.x, SDXL, and Flux model architectures. Models in safetensors or gguf (quantized) format can be loaded directly. Quantized models significantly reduce memory usage while maintaining reasonable quality. Text-to-image generates from a prompt. Image-to-image transforms an existing image guided by a prompt. The strength parameter controls how much the original image is altered. Build from source using CMake. GPU acceleration is available through CUDA, Metal, and Vulkan backends.

参数

-m, --model _FILE_
Path to model weights (.safetensors or .gguf).
-p, --prompt _TEXT_
Text prompt for image generation.
-n, --negative-prompt _TEXT_
Negative prompt to guide away from.
-o, --output _FILE_
Output image path.
--steps _N_
Number of sampling steps (default: 20).
--cfg-scale _FLOAT_
Classifier-free guidance scale (default: 7.0).
--seed _INT_
RNG seed (-1 for random).
--width _PX_
Image width in pixels.
--height _PX_
Image height in pixels.
--sampling-method _METHOD_
Sampling method: euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, lcm.
--img2img _FILE_
Input image for image-to-image generation.
--strength _FLOAT_
Denoising strength for img2img (0.0-1.0).
--threads _N_
Number of CPU threads.
--rng _TYPE_
RNG type: std_default, cuda.

FAQ

What is the sd-cli command used for?

sd-cli is the command-line interface for stable-diffusion.cpp, a lightweight C/C++ implementation of Stable Diffusion using the ggml tensor library. It runs image generation models on CPU and GPU without requiring Python or heavy ML frameworks. The tool supports Stable Diffusion 1.x, 2.x, SDXL, and Flux model architectures. Models in safetensors or gguf (quantized) format can be loaded directly. Quantized models significantly reduce memory usage while maintaining reasonable quality. Text-to-image generates from a prompt. Image-to-image transforms an existing image guided by a prompt. The strength parameter controls how much the original image is altered. Build from source using CMake. GPU acceleration is available through CUDA, Metal, and Vulkan backends.

How do I run a basic sd-cli example?

Run `sd-cli -m [model.safetensors] -p "[a photo of a cat]" -o [output.png]` in a terminal, then adjust file names, paths, flags, or remote targets for your system.

What does -m, --model _FILE_ do in sd-cli?

Path to model weights (.safetensors or .gguf).