cneural / fastcomposer-t4
- Public
- 15 runs
-
T4
Run cneural/fastcomposer-t4 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 |
|---|---|---|---|
| image1 |
string
|
First input image
|
|
| image2 |
string
|
Second input image, optional
|
|
| prompt |
string
|
A man img and a man img singing in the park together.
|
Input proper text prompts, such as "A woman img and a man img in the snow" or "A painting of a man img in the style of Van Gogh", where "img" specifies the token you want to augment and comes after the word.
|
| alpha |
number
|
0.7
Max: 1 |
A smaller alpha aligns images with text better, but may deviate from the subject image. Increase alpha to improve identity preservation, decrease it for prompt consistency.
|
| num_steps |
integer
|
50
Min: 1 Max: 300 |
Number of diffusion steps
|
| num_images_per_prompt |
integer
|
1
Min: 1 Max: 4 |
Number of output images. Lower this setting if OOM.
|
| guidance_scale |
number
|
5
Min: 1.5 Max: 50 |
Scale for classifier-free guidance.
|
| width |
integer
|
512
|
Width of output image.
|
| height |
integer
|
512
|
Height of output image.
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed.
|
{
"type": "object",
"title": "Input",
"required": [
"image1"
],
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 9,
"description": "Random seed. Leave blank to randomize the seed."
},
"alpha": {
"type": "number",
"title": "Alpha",
"default": 0.7,
"maximum": 1,
"minimum": 0,
"x-order": 3,
"description": "A smaller alpha aligns images with text better, but may deviate from the subject image. Increase alpha to improve identity preservation, decrease it for prompt consistency."
},
"width": {
"type": "integer",
"title": "Width",
"default": 512,
"x-order": 7,
"description": "Width of output image."
},
"height": {
"type": "integer",
"title": "Height",
"default": 512,
"x-order": 8,
"description": "Height of output image."
},
"image1": {
"type": "string",
"title": "Image1",
"format": "uri",
"x-order": 0,
"description": "First input image"
},
"image2": {
"type": "string",
"title": "Image2",
"format": "uri",
"x-order": 1,
"description": "Second input image, optional"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "A man img and a man img singing in the park together.",
"x-order": 2,
"description": "Input proper text prompts, such as \"A woman img and a man img in the snow\" or \"A painting of a man img in the style of Van Gogh\", where \"img\" specifies the token you want to augment and comes after the word."
},
"num_steps": {
"type": "integer",
"title": "Num Steps",
"default": 50,
"maximum": 300,
"minimum": 1,
"x-order": 4,
"description": "Number of diffusion steps"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 5,
"maximum": 50,
"minimum": 1.5,
"x-order": 6,
"description": "Scale for classifier-free guidance."
},
"num_images_per_prompt": {
"type": "integer",
"title": "Num Images Per Prompt",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 5,
"description": "Number of output images. Lower this setting if OOM."
}
}
}
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"
}