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lightweight-ai /model3_5_0:dee31edb
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 bohemian-style female travel blogger with sun-kissed skin and messy beach waves
|
Prompt for generated image
|
| negative_prompt |
string
|
|
negative prompt
|
| scheduler |
None
|
K_EULER
|
scheduler
|
| image |
string
|
Upload an image for inpainting. This will be the base image that will be partially modified.
|
|
| guidance_scale |
number
|
3.5
|
None
|
| inpaint |
boolean
|
False
|
None
|
| controlnet |
boolean
|
False
|
None
|
| mask |
string
|
Upload a mask image for inpainting. White areas (255) indicate regions to be inpainted, while black areas (0) will be preserved from the original image.
|
|
| width |
integer
|
1024
|
Width of output image
|
| height |
integer
|
1024
|
Height of output image
|
| prompt_strength |
number
|
0.8
Max: 1 |
Prompt strength (or denoising strength) when using image to image. 1.0 corresponds to full destruction of information in image.
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
| num_inference_steps |
integer
|
28
Min: 1 Max: 50 |
Number of inference steps
|
| loras |
array
|
[]
|
Lora list (Realism, Karina, IU)
|
| lora_scales |
array
|
[]
|
Lora scales
|
| seed |
integer
|
Random seed. Set for reproducible generation
|
|
| output_format |
None
|
png
|
Format of the output images
|
| output_quality |
integer
|
100
Max: 100 |
Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
|
| control_type |
None
|
canny
|
Control type
|
| control_image |
string
|
Control image
|
|
| control_strength |
number
|
0.2
Max: 1 |
None
|
| low_threshold |
integer
|
100
|
None
|
| high_threshold |
integer
|
200
|
None
|
| nsfw_chekcer |
boolean
|
False
|
None
|
| sketch_image |
string
|
Control image
|
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'}