zsxkib / prototype-model

A test model (instantid)

  • Public
  • 641 runs

Run zsxkib/prototype-model with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

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
{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}