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Run Stable Diffusion XL as a serverless endpoint to generate images.

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Usage

The worker accepts the following input parameters:

Parameter	Type	Default	Required	Description
prompt	str	None	Yes*	The main text prompt describing the desired image.
negative_prompt	str	None	No	Text prompt specifying concepts to exclude from the image
height	int	1024	No	The height of the generated image in pixels
width	int	1024	No	The width of the generated image in pixels
seed	int	None	No	Random seed for reproducibility. If None, a random seed is generated
scheduler	str	'DDIM'	No	The noise scheduler to use. Options include PNDM, KLMS, DDIM, K_EULER, DPMSolverMultistep
num_inference_steps	int	25	No	Number of denoising steps for the base model
refiner_inference_steps	int	50	No	Number of denoising steps for the refiner model
guidance_scale	float	7.5	No	Classifier-Free Guidance scale. Higher values lead to images closer to the prompt, lower values more creative
strength	float	0.3	No	The strength of the noise added when using an image_url for image-to-image or refinement
image_url	str	None	No	URL of an initial image to use for image-to-image generation (runs only refiner). If None, performs text-to-image
num_images	int	1	No	Number of images to generate per prompt (Constraint: must be 1 or 2)
high_noise_frac	float	None	No	Fraction of denoising steps performed by the base model (e.g., 0.8 for 80%). denoising_end for base

Note

prompt is required unless image_url is provided

Example Request

{
  "input": {
    "prompt": "A majestic steampunk dragon soaring through a cloudy sky, intricate clockwork details, golden hour lighting, highly detailed",
    "negative_prompt": "blurry, low quality, deformed, ugly, text, watermark, signature",
    "height": 1024,
    "width": 1024,
    "num_inference_steps": 25,
    "refiner_inference_steps": 50,
    "guidance_scale": 7.5,
    "strength": 0.3,
    "high_noise_frac": 0.8,
    "seed": 42,
    "scheduler": "K_EULER",
    "num_images": 1
  }
}

which is producing an output like this:

{
  "delayTime": 11449,
  "executionTime": 6120,
  "id": "447f10b8-c745-4c3b-8fad-b1d4ebb7a65b-e1",
  "output": {
    "image_url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAAQACAIAAADwf7zU...",
    "images": [
      "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAAQACAIAAADwf7zU..."
    ],
    "seed": 42
  },
  "status": "COMPLETED",
  "workerId": "462u6mrq9s28h6"
}

and when you convert the base64-encoded image into an actual image, it looks like this: