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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
|
Modern skyscraper, glass facade, urban skyline, clear day.
|
Input prompt
|
| suffix_prompt |
string
|
Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece
|
Additional prompt
|
| negative_prompt |
string
|
Dull and Lifeless Colors, Poor Lighting, Blurred and Unfocused, Overexposed Highlights, Crowded and Cluttered, Distorted Perspective, Gritty Texture, low res, draft, cgi, low quality render, thumbnail
|
Input Negative Prompt
|
| image |
string
|
Input image for img2img or inpaint mode
|
|
| width |
integer
|
1024
|
Width of output image
|
| height |
integer
|
1024
|
Height of output image
|
| generate_square |
boolean
|
False
|
Whether generate square image, assert height == width
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
| num_inference_steps |
integer
|
35
Min: 1 Max: 500 |
Number of denoising steps
|
| guidance_scale |
number
|
7.5
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
| adapter_conditioning_scale |
number
|
0.9
Max: 2 |
Scale for adapter module
|
| seed |
integer
|
0
|
Random seed. Enter 0 to randomize the seed
|
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'}