vectradmin
/
sdxl-v
- Public
- 36.9K runs
Run vectradmin/sdxl-v 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
|
1girl, masterpiece, best quality, sharp focus, highly detailed, dynamic lighting, vivid colors, texture detail, particle effects, subject-background isolation, storytelling elements, narrative flair, 16k, HDR
|
Input Prompt
|
| neg_prompt |
string
|
deformed iris, deformed pupils, gaussian, noise, worst quality, lowres, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art, blur, blurry, grainy, morbid, ugly, asymmetrical, mutated, malformed, mutilated, poorly lit, bad shadow, draft, cropped out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, pixelated, soft focus, color fringing, overprocessed, oversharpened
|
Input Negative Prompt
|
| width |
integer
(enum)
|
1024
Options: 512, 576, 640, 704, 768, 832, 896, 960, 1024, 1088, 1152, 1216, 1280, 1344, 1408, 1472, 1536 |
Width of Output Image
|
| height |
integer
(enum)
|
1024
Options: 512, 576, 640, 704, 768, 832, 896, 960, 1024, 1088, 1152, 1216, 1280, 1344, 1408, 1472, 1536 |
Height of Output Image
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of Images to Output
|
| scheduler |
string
(enum)
|
DPMSolverMultistep
Options: LCM, DDIM, DPMSolverMultistep, K_EULER, K_EULER_ANCESTRAL, PNDM, KLMS |
Choose a Scheduler
|
| num_inference_steps |
integer
|
40
Min: 1 Max: 65 |
Number of Denoising Steps
|
| guidance_scale |
number
|
3.6
Min: 0.1 Max: 5 |
Scale for Classifier-free Guidance
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| use_lcm |
boolean
|
False
|
Whether to use LCM-LoRA, if using, suggested num_inference_steps 2-8, guidance_scale 1.0-2.0
|
| ping_flag |
boolean
|
False
|
Check Status
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 8,
"description": "Random seed. Leave blank to randomize the seed"
},
"width": {
"enum": [
512,
576,
640,
704,
768,
832,
896,
960,
1024,
1088,
1152,
1216,
1280,
1344,
1408,
1472,
1536
],
"type": "integer",
"title": "width",
"description": "Width of Output Image",
"default": 1024,
"x-order": 2
},
"height": {
"enum": [
512,
576,
640,
704,
768,
832,
896,
960,
1024,
1088,
1152,
1216,
1280,
1344,
1408,
1472,
1536
],
"type": "integer",
"title": "height",
"description": "Height of Output Image",
"default": 1024,
"x-order": 3
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "1girl, masterpiece, best quality, sharp focus, highly detailed, dynamic lighting, vivid colors, texture detail, particle effects, subject-background isolation, storytelling elements, narrative flair, 16k, HDR",
"x-order": 0,
"description": "Input Prompt"
},
"use_lcm": {
"type": "boolean",
"title": "Use Lcm",
"default": false,
"x-order": 9,
"description": "Whether to use LCM-LoRA, if using, suggested num_inference_steps 2-8, guidance_scale 1.0-2.0"
},
"ping_flag": {
"type": "boolean",
"title": "Ping Flag",
"default": false,
"x-order": 10,
"description": "Check Status"
},
"scheduler": {
"enum": [
"LCM",
"DDIM",
"DPMSolverMultistep",
"K_EULER",
"K_EULER_ANCESTRAL",
"PNDM",
"KLMS"
],
"type": "string",
"title": "scheduler",
"description": "Choose a Scheduler",
"default": "DPMSolverMultistep",
"x-order": 5
},
"neg_prompt": {
"type": "string",
"title": "Neg Prompt",
"default": "deformed iris, deformed pupils, gaussian, noise, worst quality, lowres, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art, blur, blurry, grainy, morbid, ugly, asymmetrical, mutated, malformed, mutilated, poorly lit, bad shadow, draft, cropped out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, pixelated, soft focus, color fringing, overprocessed, oversharpened",
"x-order": 1,
"description": "Input Negative Prompt"
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 4,
"description": "Number of Images to Output"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 3.6,
"maximum": 5,
"minimum": 0.1,
"x-order": 7,
"description": "Scale for Classifier-free Guidance"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 40,
"maximum": 65,
"minimum": 1,
"x-order": 6,
"description": "Number of Denoising Steps"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
{
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Output"
}