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zsxkib /prototype-model:0e7ba7da

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
image
string
Input face image
pose_image
string
(Optional) reference pose image
prompt
string
a person
Input prompt
negative_prompt
string
Input Negative Prompt
sdxl_weights
string (enum)
stable-diffusion-xl-base-1.0

Options:

stable-diffusion-xl-base-1.0, juggernaut-xl-v8, afrodite-xl-v2, albedobase-xl-20, albedobase-xl-v13, animagine-xl-30, anime-art-diffusion-xl, anime-illust-diffusion-xl, dreamshaper-xl, dynavision-xl-v0610, guofeng4-xl, nightvision-xl-0791, omnigen-xl, pony-diffusion-v6-xl, protovision-xl-high-fidel

Pick which base weights you want to use
scheduler
string (enum)
EulerDiscreteScheduler

Options:

DEISMultistepScheduler, HeunDiscreteScheduler, EulerDiscreteScheduler, DPMSolverMultistepScheduler, DPMSolverMultistepScheduler-Karras, DPMSolverMultistepScheduler-Karras-SDE

Scheduler
num_inference_steps
integer
30

Min: 1

Max: 500

Number of denoising steps
guidance_scale
number
7.5

Min: 1

Max: 50

Scale for classifier-free guidance
ip_adapter_scale
number
0.8

Max: 1.5

Scale for image adapter strength (for detail)
controlnet_conditioning_scale
number
0.8

Max: 1.5

Scale for IdentityNet strength (for fidelity)
enable_pose_controlnet
boolean
True
Enable Openpose ControlNet, overrides strength if set to false
pose_strength
number
0.4

Max: 1

Openpose ControlNet strength, effective only if `enable_pose_controlnet` is true
enable_canny_controlnet
boolean
False
Enable Canny ControlNet, overrides strength if set to false
canny_strength
number
0.3

Max: 1

Canny ControlNet strength, effective only if `enable_canny_controlnet` is true
enable_depth_controlnet
boolean
False
Enable Depth ControlNet, overrides strength if set to false
depth_strength
number
0.5

Max: 1

Depth ControlNet strength, effective only if `enable_depth_controlnet` is true
enable_lcm
boolean
False
Enable Fast Inference with LCM (Latent Consistency Models) - speeds up inference steps, trade-off is the quality of the generated image. Performs better with close-up portrait face images
lcm_num_inference_steps
integer
5

Min: 1

Max: 10

Only used when `enable_lcm` is set to True, Number of denoising steps when using LCM
lcm_guidance_scale
number
1.5

Min: 1

Max: 20

Only used when `enable_lcm` is set to True, Scale for classifier-free guidance when using LCM
enhance_nonface_region
boolean
True
Enhance non-face region
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
Random seed. Leave blank to randomize the seed
disable_safety_checker
boolean
False
Disable safety checker for generated images

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'}