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expa-ai /cloudflare-hack:2f527d61
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
|
An astronaut riding a rainbow unicorn
|
Input prompt
|
| negative_prompt |
string
|
|
Negative Prompt
|
| image |
string
|
Input image from User.
|
|
| width |
integer
|
1080
|
Width of output image
|
| height |
integer
|
144
|
Height of output image
|
| sizing_strategy |
None
|
width_height
|
Decide how to resize images – use width/height, resize based on input image or control image
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output
|
| scheduler |
None
|
K_EULER
|
scheduler
|
| num_inference_steps |
integer
|
30
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
|
|
| refine |
None
|
no_refiner
|
Which refine style to use
|
| refine_steps |
integer
|
For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
|
|
| apply_watermark |
boolean
|
True
|
Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
|
| apply_brand_bg |
boolean
|
True
|
Applies a brand background.
|
| controlnet_1 |
None
|
none
|
Controlnet
|
| controlnet_1_image |
string
|
Input image for first controlnet
|
|
| controlnet_1_conditioning_scale |
number
|
0.75
Max: 4 |
How strong the controlnet conditioning is
|
| controlnet_1_start |
number
|
0
Max: 1 |
When controlnet conditioning starts
|
| controlnet_1_end |
number
|
1
Max: 1 |
When controlnet conditioning ends
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}