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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
|
a high-resolution photograph of a big red frog on a green leaf
|
Input prompt
|
| num_images_per_prompt |
integer
(enum)
|
1
Options: 1, 4 |
Number of images to output
|
| prior_num_inference_steps |
integer
|
25
|
The number of denoising steps for the prior. More denoising steps usually lead to a higher quality image at the expense of slower inference
|
| decoder_num_inference_steps |
integer
|
25
|
The number of denoising steps for the decoder. More denoising steps usually lead to a higher quality image at the expense of slower inference
|
| super_res_num_inference_steps |
integer
|
7
|
The number of denoising steps for super resolution. More denoising steps usually lead to a higher quality image at the expense of slower inference
|
| prior_guidance_scale |
number
|
4
|
Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality
|
| decoder_guidance_scale |
number
|
8
|
Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality
|
| seed |
integer
|
Random seed. Leave blank 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'}