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pnyompen /dreamshaper-controlnet:71e176d8

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 for img2img or inpaint mode
img2img
boolean
False
Use img2img pipeline, it will use the image input both as the control image and the base image.
auto_generate_caption
boolean
False
Use BLIP to generate captions for the input images
generated_caption_weight
number
0.5
Weight for the generated caption
condition_scale
number
1.1

Max: 2

The bigger this number is, the more ControlNet interferes
strength
number
0.8

Max: 1

When img2img is active, the denoising strength. 1 means total destruction of the input image.
ip_adapter_scale
number
1
Scale for the IP Adapter
negative_prompt
string
Input Negative Prompt
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
7.5

Min: 1

Max: 50

Scale for classifier-free guidance
seed
integer
Random seed. Leave blank to randomize the seed
lora_scale
number
0.95

Max: 1

LoRA additive scale. Only applicable on trained models.
lora_weights
string
Replicate LoRA weights to use. Leave blank to use the default weights.
remove_bg
boolean
False
Remove background from the input image
remove_eye
boolean
True
Remove eye from the canny 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'}