mgonline2021
/
sdxlorarlvsn
- Public
- 127 runs
-
8x L40S
Run mgonline2021/sdxlorarlvsn 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 |
|---|---|---|---|
| num_samples |
integer
|
1
Min: 1 Max: 4 |
num_samples
|
| pose_image |
string
|
Pose image
|
|
| pose_resemblance |
number
|
0.8
Max: 1 |
Control Guidance End (0 - 1)
|
| face_image |
string
|
Face image
|
|
| face_resemblance |
number
|
0.5
Max: 1 |
Face Conditioning Scale (0 - 1)
|
| face_expanding_bbox |
number
|
0.5
Max: 1 |
Face Expanding bbox (0 - 1)
|
| prompt |
string
|
a portrait of a [MODEL] with a suit and a tie
|
None
|
| n_prompt |
string
|
|
None
|
| steps |
integer
|
8
Max: 50 |
num_inference_steps
|
| width |
integer
|
768
|
Width
|
| seed |
integer
|
0
Max: 2147483647 |
Seed (0 = random, maximum: 2147483647)
|
{
"type": "object",
"title": "Input",
"required": [
"pose_image",
"face_image"
],
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"default": 0,
"maximum": 2147483647,
"minimum": 0,
"x-order": 10,
"description": "Seed (0 = random, maximum: 2147483647)"
},
"steps": {
"type": "integer",
"title": "Steps",
"default": 8,
"maximum": 50,
"minimum": 0,
"x-order": 8,
"description": " num_inference_steps"
},
"width": {
"type": "integer",
"title": "Width",
"default": 768,
"x-order": 9,
"description": "Width"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "a portrait of a [MODEL] with a suit and a tie",
"x-order": 6
},
"n_prompt": {
"type": "string",
"title": "N Prompt",
"default": "",
"x-order": 7
},
"face_image": {
"type": "string",
"title": "Face Image",
"format": "uri",
"x-order": 3,
"description": "Face image"
},
"pose_image": {
"type": "string",
"title": "Pose Image",
"format": "uri",
"x-order": 1,
"description": "Pose image"
},
"num_samples": {
"type": "integer",
"title": "Num Samples",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 0,
"description": " num_samples"
},
"face_resemblance": {
"type": "number",
"title": "Face Resemblance",
"default": 0.5,
"maximum": 1,
"minimum": 0,
"x-order": 4,
"description": "Face Conditioning Scale (0 - 1)"
},
"pose_resemblance": {
"type": "number",
"title": "Pose Resemblance",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 2,
"description": "Control Guidance End (0 - 1)"
},
"face_expanding_bbox": {
"type": "number",
"title": "Face Expanding Bbox",
"default": 0.5,
"maximum": 1,
"minimum": 0,
"x-order": 5,
"description": "Face Expanding bbox (0 - 1)"
}
}
}
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"
}