fofr
/
lcm-profiling
- Public
- 271 runs
Run fofr/lcm-profiling 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
|
Self-portrait oil painting, a beautiful cyborg with golden hair, 8k
|
For multiple prompts, enter each on a new line.
|
| width |
integer
|
768
|
Width of output image. Lower if out of memory
|
| height |
integer
|
768
|
Height of output image. Lower if out of memory
|
| sizing_strategy |
string
(enum)
|
width/height
Options: width/height, input_image, control_image |
Decide how to resize images – use width/height, resize based on input image or control image
|
| image |
string
|
Input image for img2img
|
|
| prompt_strength |
number
|
0.8
Max: 1 |
Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
|
| num_images |
integer
|
1
Min: 1 Max: 50 |
Number of images per prompt
|
| num_inference_steps |
integer
|
8
Min: 1 Max: 50 |
Number of denoising steps. Recommend 1 to 8 steps.
|
| guidance_scale |
number
|
8
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
| lcm_origin_steps |
integer
|
50
Min: 1 |
None
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| control_image |
string
|
Image for controlnet conditioning
|
|
| controlnet_conditioning_scale |
number
|
2
Min: 0.1 Max: 4 |
Controlnet conditioning scale
|
| control_guidance_start |
number
|
0
Max: 1 |
Controlnet start
|
| control_guidance_end |
number
|
1
Max: 1 |
Controlnet end
|
| canny_low_threshold |
number
|
100
Min: 1 Max: 255 |
Canny low threshold
|
| canny_high_threshold |
number
|
200
Min: 1 Max: 255 |
Canny high threshold
|
| archive_outputs |
boolean
|
False
|
Option to archive the output images
|
| disable_safety_checker |
boolean
|
False
|
Disable safety checker for generated images. This feature is only available through the API
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 10,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 4,
"description": "Input image for img2img"
},
"width": {
"type": "integer",
"title": "Width",
"default": 768,
"x-order": 1,
"description": "Width of output image. Lower if out of memory"
},
"height": {
"type": "integer",
"title": "Height",
"default": 768,
"x-order": 2,
"description": "Height of output image. Lower if out of memory"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
"x-order": 0,
"description": "For multiple prompts, enter each on a new line."
},
"num_images": {
"type": "integer",
"title": "Num Images",
"default": 1,
"maximum": 50,
"minimum": 1,
"x-order": 6,
"description": "Number of images per prompt"
},
"control_image": {
"type": "string",
"title": "Control Image",
"format": "uri",
"x-order": 11,
"description": "Image for controlnet conditioning"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 8,
"maximum": 20,
"minimum": 1,
"x-order": 8,
"description": "Scale for classifier-free guidance"
},
"archive_outputs": {
"type": "boolean",
"title": "Archive Outputs",
"default": false,
"x-order": 17,
"description": "Option to archive the output images"
},
"prompt_strength": {
"type": "number",
"title": "Prompt Strength",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 5,
"description": "Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image"
},
"sizing_strategy": {
"enum": [
"width/height",
"input_image",
"control_image"
],
"type": "string",
"title": "sizing_strategy",
"description": "Decide how to resize images \u2013 use width/height, resize based on input image or control image",
"default": "width/height",
"x-order": 3
},
"lcm_origin_steps": {
"type": "integer",
"title": "Lcm Origin Steps",
"default": 50,
"minimum": 1,
"x-order": 9
},
"canny_low_threshold": {
"type": "number",
"title": "Canny Low Threshold",
"default": 100,
"maximum": 255,
"minimum": 1,
"x-order": 15,
"description": "Canny low threshold"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 8,
"maximum": 50,
"minimum": 1,
"x-order": 7,
"description": "Number of denoising steps. Recommend 1 to 8 steps."
},
"canny_high_threshold": {
"type": "number",
"title": "Canny High Threshold",
"default": 200,
"maximum": 255,
"minimum": 1,
"x-order": 16,
"description": "Canny high threshold"
},
"control_guidance_end": {
"type": "number",
"title": "Control Guidance End",
"default": 1,
"maximum": 1,
"minimum": 0,
"x-order": 14,
"description": "Controlnet end"
},
"control_guidance_start": {
"type": "number",
"title": "Control Guidance Start",
"default": 0,
"maximum": 1,
"minimum": 0,
"x-order": 13,
"description": "Controlnet start"
},
"disable_safety_checker": {
"type": "boolean",
"title": "Disable Safety Checker",
"default": false,
"x-order": 18,
"description": "Disable safety checker for generated images. This feature is only available through the API"
},
"controlnet_conditioning_scale": {
"type": "number",
"title": "Controlnet Conditioning Scale",
"default": 2,
"maximum": 4,
"minimum": 0.1,
"x-order": 12,
"description": "Controlnet conditioning scale"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{
"type": "array",
"items": {
"type": "string"
},
"title": "Output"
}