blendto / sdxl-controlnet-xformers

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  • 3K runs

Run blendto/sdxl-controlnet-xformers with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field Type Default value Description
prompt1
string
Input prompt
prompt2
string
Input prompt
prompt3
string
Input prompt
prompt4
string
Input prompt
negative_prompt
string
Input Negative Prompt
image1
string
Input image for img2img or inpaint mode
image2
string
Input image for img2img or inpaint mode
image3
string
Input image for img2img or inpaint mode
image4
string
Input image for img2img or inpaint mode
width1
integer
1024
Width of output image
height1
integer
1024
Height of output image
height2
integer
1024
Height of output image
width2
integer
1024
Width of output image
height3
integer
1024
Height of output image
width3
integer
1024
Width of output image
height4
integer
1024
Height of output image
width4
integer
1024
Width of output image
scheduler
string (enum)
K_EULER

Options:

DDIM, DPMSolverMultistep, HeunDiscrete, KarrasDPM, K_EULER_ANCESTRAL, K_EULER, PNDM, UNIPC

scheduler
num_inference_steps
integer
50

Min: 1

Max: 500

Number of denoising steps
guidance_scale
number
7.5

Min: 1

Max: 50

Scale for classifier-free guidance
seed
integer
Random seed. Leave blank to randomize the seed
controlnet_conditioning_scale
number
0.6

Max: 1

ControlNet conditioning scale. Only applicable on trained models.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}