fater-ai / lr-df-v0.1
- Public
- 19 runs
Run fater-ai/lr-df-v0.1 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
|
Tall man, walking, high quality, 8k
|
Text prompt for image generation
|
| negative_prompt |
string
|
|
Negative prompt to avoid undesired features
|
| num_inference_steps |
integer
|
25
Min: 1 |
Number of denoising steps
|
| guidance_scale |
number
|
7
|
Guidance scale for classifier-free guidance
|
| seed |
integer
|
12345
|
Random seed for reproducibility
|
| strength |
number
|
1
Max: 1 |
Strength of transformation (0 to 1)
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"default": 12345,
"x-order": 4,
"description": "Random seed for reproducibility"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "Tall man, walking, high quality, 8k",
"x-order": 0,
"description": "Text prompt for image generation"
},
"strength": {
"type": "number",
"title": "Strength",
"default": 1,
"maximum": 1,
"minimum": 0,
"x-order": 5,
"description": "Strength of transformation (0 to 1)"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7,
"minimum": 0,
"x-order": 3,
"description": "Guidance scale for classifier-free guidance"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "",
"x-order": 1,
"description": "Negative prompt to avoid undesired features"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 25,
"minimum": 1,
"x-order": 2,
"description": "Number of denoising 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"
}