hardikdava / f_dd
- Public
- 9 runs
Run hardikdava/f_dd 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
|
Text prompt
|
|
| input_image |
string
|
Input image
|
|
| mask_image |
string
|
Input mask
|
|
| guidance_scale |
number
|
3.5
Max: 30 |
Guidance scale
|
| strength |
number
|
0.8
Max: 1 |
Img2Img strength
|
| num_inference_steps |
integer
|
28
Min: 1 Max: 28 |
Number of inference steps
|
| lora_url |
string
|
URL of the trained lora
|
|
| lora_stength |
number
|
0.8
Max: 1 |
Lora strength
|
{
"type": "object",
"title": "Input",
"required": [
"prompt"
],
"properties": {
"prompt": {
"type": "string",
"title": "Prompt",
"x-order": 0,
"description": "Text prompt"
},
"lora_url": {
"type": "string",
"title": "Lora Url",
"x-order": 6,
"description": "URL of the trained lora"
},
"strength": {
"type": "number",
"title": "Strength",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 4,
"description": "Img2Img strength"
},
"mask_image": {
"type": "string",
"title": "Mask Image",
"format": "uri",
"x-order": 2,
"description": "Input mask"
},
"input_image": {
"type": "string",
"title": "Input Image",
"format": "uri",
"x-order": 1,
"description": "Input image"
},
"lora_stength": {
"type": "number",
"title": "Lora Stength",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 7,
"description": "Lora strength"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 3.5,
"maximum": 30,
"minimum": 0,
"x-order": 3,
"description": "Guidance scale"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 28,
"maximum": 28,
"minimum": 1,
"x-order": 5,
"description": "Number of inference steps"
}
}
}
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"
}