expa-ai / tile-upscale

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  • 1 run

Run expa-ai/tile-upscale 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
prompt
string
Prompt for the model
image
string
Image for scribble controlnet
ctrl_image
string
Control image for scribble controlnet
resolution
integer (enum)
2048

Options:

2048, 2560

Image resolution
resemblance
number
0.5

Max: 1

Conditioning scale for controlnet
creativity
number
0.5

Max: 1

Denoising strength. 1 means total destruction of the original image
hdr
number
0

Max: 1

HDR improvement over the original image
scheduler
string (enum)
DDIM

Options:

DDIM, DPMSolverMultistep, K_EULER_ANCESTRAL, K_EULER

Choose a scheduler.
steps
integer
20
Steps
guidance_scale
number
7

Min: 0.1

Max: 30

Scale for classifier-free guidance
seed
integer
Seed
negative_prompt
string
teeth, tooth, open mouth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant
Negative prompt
guess_mode
boolean
False
In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.

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"
}