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tstramer /mo-di-diffusion:2ba6ef02
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
|
|
Input prompt
|
width |
integer
(enum)
|
512
Options: 128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024 |
Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
|
height |
integer
(enum)
|
512
Options: 128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024 |
Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
|
init_image |
string
|
Inital image to generate variations of. Will be resized to the specified width and height
|
|
mask |
string
|
Black and white image to use as mask for inpainting over init_image. Black pixels are inpainted and white pixels are preserved. Tends to work better with prompt strength of 0.5-0.7. Consider using https://replicate.com/andreasjansson/stable-diffusion-inpainting instead.
|
|
prompt_strength |
number
|
0.8
|
Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image
|
num_outputs |
integer
|
1
Min: 1 Max: 10 |
Number of images to output. If the NSFW filter is triggered, you may get fewer outputs than this.
|
num_inference_steps |
integer
|
50
Min: 1 Max: 500 |
Number of denoising steps
|
guidance_scale |
number
|
7.5
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
scheduler |
string
(enum)
|
K-LMS
Options: DDIM, K-LMS, PNDM |
Choose a scheduler. If you use an init image, PNDM will be used
|
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'}