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raffamelena /cog-sdxl:94610504
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 |
---|---|---|---|
model |
string
(enum)
|
xl_aumix
Options: xl_aumix, xl_mm, xl_pony |
The model to use
|
vae |
string
(enum)
|
default
Options: default, xl_aumix, xl_mm, xl_pony |
The VAE to use
|
prompt |
string
|
1girl
|
The prompt
|
image |
string
|
The image for image to image or as the base for inpainting (Will be scaled then cropped to the set width and height)
|
|
mask |
string
|
The mask for inpainting, white areas will be modified and black preserved (Will be scaled then cropped to the set width and height)
|
|
loras |
string
|
The LoRAs to use, must be either a string with format "URL:Strength,URL:Strength,..." (Strength is optional, default to 1), or a JSON list dumped as a string containing key "url" (Required), "strength" (Optional, default to 1), and "civitai_token" (Optional, for downloading from CivitAI) (NOTICE: Will download the weights, might take a while if the LoRAs are huge or the download is slow, WILL CHARGE WHEN DOWNLOADING)
|
|
negative_prompt |
string
|
animal, cat, dog, big breasts
|
The negative prompt (For things you don't want)
|
cfg_scale |
number
|
7
Min: 1 Max: 50 |
CFG Scale defines how much attention the model pays to the prompt when generating
|
guidance_rescale |
number
|
0.7
Max: 5 |
The amount to rescale CFG generated noise to avoid generating overexposed images
|
clip_skip |
integer
|
1
Min: 1 |
How many CLIP layers to skip, 1 is actually no skip, this is the behavior in A1111 so it's aligned to it
|
width |
integer
|
1184
Min: 1 Max: 4096 |
The width of the image
|
height |
integer
|
864
Min: 1 Max: 4096 |
The height of the image
|
prepend_preprompt |
boolean
|
True
|
Prepend preprompt (Prompt: "score_9, score_8_up, score_7_up, " Negative prompt: "score_4, score_3, score_2, score_1, worst quality, bad hands, bad feet, ")
|
scheduler |
string
(enum)
|
DPM++ 2M SDE Karras
Options: DPM++ 2M SDE Karras, UniPC, Heun, DDIM, DPM2 a, DPM2 a Karras, DPM SDE, DDPM, DPM++ SDE, DPM++ SDE Karras, LMS, LMS Karras, Euler a, Euler, PNDM, DPM2, DPM2 Karras, DEIS, DPM++ 2M, DPM++ 2M Karras, DPM++ 2M SDE |
The scheduler to use
|
steps |
integer
|
35
Min: 1 Max: 100 |
The steps when generating
|
strength |
number
|
0.7
Max: 1 |
How much noise to add (For image to image and inpainting only, larger value indicates more noise added to the input image)
|
blur_factor |
number
|
5
|
The factor to blur the inpainting mask for smoother transition between masked and unmasked
|
batch_size |
integer
|
1
Min: 1 Max: 4 |
Number of images to generate (1-4)
|
seed |
integer
|
-1
|
The seed used when generating, set to -1 for random seed
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}