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aramintak /painting-light:930beafe
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
|
|
None
|
| negative_prompt |
string
|
|
Things you do not want to see in your image
|
| number_of_images |
integer
|
1
Min: 1 Max: 10 |
Number of images to generate
|
| width |
integer
|
1024
|
None
|
| height |
integer
|
1024
|
None
|
| lora_strength |
number
|
1
Max: 3 |
Strength of the lora to use for the generation. Default is 1.0.
|
| output_format |
string
(enum)
|
webp
Options: webp, jpg, png |
Format of the output images
|
| output_quality |
integer
|
80
Max: 100 |
Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.
|
| seed |
integer
|
Set a seed for reproducibility. Random by default.
|
|
| disable_safety_checker |
boolean
|
False
|
Disable safety checker for generated images.
|
| sampler |
string
(enum)
|
Default
Options: Default, euler, euler_ancestral, heun, heunpp2, dpm_2, dpm_2_ancestral, lms, dpm_fast, dpm_adaptive, dpmpp_2s_ancestral, dpmpp_sde, dpmpp_sde_gpu, dpmpp_2m, dpmpp_2m_sde, dpmpp_2m_sde_gpu, dpmpp_3m_sde, dpmpp_3m_sde_gpu, ddpm, lcm, ddim, uni_pc, uni_pc_bh2 |
Advanced. Change the sampler used for generation. Default is what we think gives the best images.
|
| scheduler |
string
(enum)
|
Default
Options: Default, normal, karras, exponential, sgm_uniform, simple, ddim_uniform |
Advanced. Change the scheduler used for generation. Default is what we think gives the best images.
|
| steps |
integer
|
Min: 1 Max: 50 |
Advanced. Leave empty to use recommended steps. Set it only if you want to customise the number of steps to run the sampler for.
|
| cfg |
number
|
Max: 20 |
Advanced. Leave empty to use recommended CFG (classifier free guidance). This changes how much the prompt influences the output. Set it only if you want to customise.
|
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'}