replicategithubwc
/
dreamshaper
- Public
- 1.5K runs
Run replicategithubwc/dreamshaper 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 |
|---|---|---|---|
| prompt |
string
|
a photo of an astronaut riding a horse on mars
|
Input prompt
|
| negative_prompt |
string
|
Specify things to not see in the output
|
|
| width |
integer
|
786
|
Width of output image
|
| height |
integer
|
786
|
Height of output image
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
| num_inference_steps |
integer
|
50
Min: 1 Max: 500 |
Number of denoising steps
|
| guidance_scale |
number
|
7.5
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
| scheduler |
string
(enum)
|
DPMSolverMultistep
Options: DDIM, K_EULER, DPMSolverMultistep, K_EULER_ANCESTRAL, PNDM, KLMS, UniPCMultistep, DDPM, LMSDiscrete, EulerDiscrete, EulerAncestralDiscrete, HeunDiscrete, DPM++_SDE_Karras |
Choose a scheduler.
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 8,
"description": "Random seed. Leave blank to randomize the seed"
},
"width": {
"type": "integer",
"title": "Width",
"default": 786,
"x-order": 2,
"description": "Width of output image"
},
"height": {
"type": "integer",
"title": "Height",
"default": 786,
"x-order": 3,
"description": "Height of output image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "a photo of an astronaut riding a horse on mars",
"x-order": 0,
"description": "Input prompt"
},
"scheduler": {
"enum": [
"DDIM",
"K_EULER",
"DPMSolverMultistep",
"K_EULER_ANCESTRAL",
"PNDM",
"KLMS",
"UniPCMultistep",
"DDPM",
"LMSDiscrete",
"EulerDiscrete",
"EulerAncestralDiscrete",
"HeunDiscrete",
"DPM++_SDE_Karras"
],
"type": "string",
"title": "scheduler",
"description": "Choose a scheduler.",
"default": "DPMSolverMultistep",
"x-order": 7
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 4,
"description": "Number of images to output."
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7.5,
"maximum": 20,
"minimum": 1,
"x-order": 6,
"description": "Scale for classifier-free guidance"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"x-order": 1,
"description": "Specify things to not see in the output"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 50,
"maximum": 500,
"minimum": 1,
"x-order": 5,
"description": "Number of denoising steps"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
{
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Output"
}