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batouresearch /magic-style-transfer:3b5fa5d3
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
|
image |
string
|
Input image
|
|
ip_image |
string
|
Input image for img2img or inpaint mode
|
|
condition_depth_scale |
number
|
0.35
Max: 2 |
The bigger this number is, the more ControlNet interferes
|
condition_canny_scale |
number
|
0.15
Max: 2 |
The bigger this number is, the more ControlNet interferes
|
lora_scale |
number
|
0.9
Max: 1 |
LoRA additive scale. Only applicable on trained models.
|
ip_scale |
number
|
0.3
Max: 1 |
IP Adapter strength.
|
strength |
number
|
0.9
Max: 1 |
When img2img is active, the denoising strength. 1 means total destruction of the input image.
|
negative_prompt |
string
|
|
Input Negative Prompt
|
background_color |
string
|
#A2A2A2
|
When passing an image with alpha channel, it will be replaced with this color
|
resizing_scale |
number
|
1
Min: 1 Max: 10 |
If you want the image to have a solid margin. Scale of the solid margin. 1.0 means no resizing.
|
num_inference_steps |
integer
|
30
Min: 1 Max: 500 |
Number of denoising steps
|
num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output
|
scheduler |
string
(enum)
|
K_EULER
Options: DDIM, DPMSolverMultistep, HeunDiscrete, KarrasDPM, K_EULER_ANCESTRAL, K_EULER, PNDM |
scheduler
|
guidance_scale |
number
|
4
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
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.
|
lora_weights |
string
|
Replicate LoRA weights to use. Leave blank to use the default weights.
|
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'}